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1. Introduction
Since a long time ago health sciences and natural products have been linked by the use of remedies and poisons, and nowadays there is little doubt that humans used natural drugs long before the emergence of written history [1,2]. The Ebers Papyrus dating from about 1600 BC, is one of the oldest medical treatise, which documents natural product-derived drugs used by the Sumerians and Akkadians in the 3rd century BC. Today there is information on medicinal plants dating back over about 500 years, as documented in herbaria. Laboratory studies of medicinal natural products started only about 200 years ago, with the isolation of of morphine, an alkaloid, from opium (Papaver spp.) [2,3].
Aspisoperma genus (Apocynaceae) species are trees of a great diversity of sizes that grow in different habitats and are distributed mainly among the Americas; In Brazil about 50 species of this genus have been catalogued [4–6]. There are several reports in the literature concerning the folk utilization of plants of this genus, as in treatment of malaria, dysentery, appendicitis, wounds, fever, dyspnea, asthma, scabies, stomachache, cough, constipation, boils, rheumatism, leishmaniasis, toothache, urinary tract inflammation and dermatitis. However several studies show that some plants of the genus are not recommended for pregnant women because of their potential abortifacient and teratogenic effects [7–28].
Given the diversity of popular uses of plants of the genus Aspidosperma as well as the predominance of terpenoid-alkaloids production in this genus and the importance of these substances for organic synthesis, medicinal chemistry and for knowledge of the biosynthetic pathways used by plants to produce them, we propose to review the literature concerning the aspidosperma-type terpenoid-alkaloids chemical synthesis and their biological potential.
2. Biosynthesis of Aspidosperma terpenoid alkaloids
The isolation of alkaloids from species of Aspidosperma trees and their structural elucidation give rise to theories that attempt to explain their biosynthetic origin. In the field of indole-type alkaloids, one of the earliest theories to explain its biosynthesis arose in 1933, proposing that this type of alkaloid has origin in the reaction between tryptophan, phenylalanine and glicine (although at the time the proposed structures do not represent exactly the known reality today) [29]. Revisions of this theory lead to a new biosynthetic route, proposing that the indole-type alkaloids are derived from shikimic and prephenic acids and their interactions with seco-prephenate-formadehyde units and aromatic aminoacids as tryptamine and tryptophan (figure 1) [30,31]. As Aspidosperma type alkaloids were isolated theories that tried to explain their biosynthetic origin began to emerge, which, at this moment, were based on the chemical synthesis of such alkaloids, as done by several research groups [32].
Figure 1.
Early propositions for indole alkaloid precursors.
Early work on proof of terpenoid alkaloid biosynthesis were based on administration of deuterium-labelled precursors of alkaloids to the plants tested and analysis of the metabolites produced to confirm a proposed biosynthetic way. The earliest proposition for the biosynthesis of Aspidosperma terpenoid alkaloids was the synthesis via mevalonate pathway, demonstrated in 1966 by the administration of 1-[²H2]-geraniol and 2-¹4C-geraniol to Vinca rosea and mass spectrometry detection of labeled vindoline, what allowed the proposition of the biosynthetic route showed in figure 2 [33,34]. This biosynthetic way was refined two years later with the demonstration that administration of 14C-labelled loganin (produced by the administration of 2-¹4C-geraniol to Meyanthes trifoliata) to V. rosea and Rawfolia serpentina allowed the isolation of 14C-labeled catharantine, serpentine, ajmalicine, vindoline and perivine [35], whose biosynthetic mechanism was detailed elsewhere [36–47].
Figure 2.
Proposal to Aspidosperma terpenoid alkaloid biosynthesis (adapted from [1-2]).
3. Chemical synthesis of Aspidosperma terpenoid alkaloids
Since the structure elucidation of the first isolated Aspidosperma alkaloids, various alternatives and techniques have emerged, due mainly the great structural complexity of this family of alkaloids. One of the earliest syntheses of an Aspidosperma alkaloid was published by a group from Havard University in 1959, which obtained the recently-isolated alkaloid ellipticine from condensation of indole with 3-acetylpyridine followed by reduction and pyrolisis, as shown in figure 3 [48].
Figure 3.
First synthesis of ellipticine.
Many years later, a new synthesis of aspidosperma-type skeleton was published, in a very simple way using four steps (figure 4) [49]. Another example is the synthesis of quebrachamine, one way published in 1966, and another three ways, one of them based on alkylation of cyclic enamines, other starting with 1,3-propanediol and another based on the cleavage of a thioketal group (figure 5) [50–53].
Figure 4.
Synthesis of 3-Methylaspidospermidine (adapted from [49]).
Figure 5.
Total synthesis of quebrachamine.
Despite the many synthetic routes described for obtaining quebrachamine, none was obtained with enantiomeric purity until the problem was addressed in 1980, with the development of a synthetic route to (+)-quebrachamine using L-glutamic acid as a chiral template (figure 6) [54].
Figure 6.
Enantioselective total synthesis of quebrachamine
Enamines were also utilized in the synthesis of aspidospermine, as showed in 1971 by a group from Rice University (figure 7) and other groups [55,56].
Figure 7.
Synthesis of aspidospermine.
In 1978 was published a work that introduced a conceptually new approach to the synthesis of Aspidosperma-type alkaloids, the photocyclization-rearrangement or heteroatom directed photoarylation of anilinocyclohexanones, exemplified by the synthesis of the indolines A and B shown in figure 8 [57], this concept being expanded many years later, with the demonstration of different techniques of photo-induced reactions [58–60].
Figure 8.
Photoarylation in the synthesis of Aspidosperma-type substructures.
Given the biosynthetic route proposed by Wenkert [30], a group from Yale University developed a synthetic route for obtaining the alkaloid minovine in a biogenetically modeled way (figure 9), refined many years later by the same group [61,62].
Figure 9.
Synthesis of minovine.
Based on the fact that the Aspidosperma alkaloids share common structural features, a group from the Chinese Academy of Synthesis developed a strategy to aspidophytine enantioselective and stereo-controlled synthesis that could be applied to the synthesis of several other alkaloids of this family by simply varying the initial aniline (figure 10) [63].
Figure 10.
Aspidophytine synthesis (adapted from [63]).
Another powerful technique for the Aspidosperma alkaloids skeleton is the utilization of aza-Cope rearrangements, utilized for the first time in 1981 for the stereoselective synthesis of 9a-arylhydrolilolidines precursors of vindoline (figure 11) and later expanded to other alkaloids [64–66].
Figure 11.
Application of aza-Cope rearrangement (adapted from [64]).
Based on the premise that Heck reaction is a powerful method for the construction of quaternary carbon centers, researchers from Kyoto University decided to apply this methodology to the entantioselective synthesis of (-)-epieburnamonine (figure 12) [67].
Figure 12.
Utilization of Heck reaction on the construction of intermediates in terpenoid alkaloids synthesis (adapted from [67]).
Exploiting the possibilities of C-H bond functionalization on the pyrrole ring, a group from Cambridge University recently proposed the total synthesis of rhanizilam-type alkaloids as precursors to Aspidosperma-type alkaloids, as shown in figure 13 [68].
Figure 13.
Metal-catalyzed C-H bond functionalization on terpenoid alkaloid synthesis (adapted from [68]).
3.1. Aspidosperma alkaloid precursors
Another field of great interest is in synthesis of precursors which can serve to the achieve greater structural diversity from common structures. Various approaches have been utilized in this field, such as ketone annelation of endocyclic enamines [69] (figure 14) and the utilization of photochemistry with the one pot synthesis of a 9-membered ring system that could be applied not only in the synthesis of Aspidosperma-type alkaloids, but also Strychnos, Schizozygane and Eburnamine-types, as shown in figure 15 [70].
Figure 14.
Ketone annelation of endocyclic enamines on the synthesis of alkaloids.
Figure 15.
Photochemistry on the synthesis of alkaloids.
Another approach relied on the conversion of para-substituted anisoles into 4,4-dissubstitued cyclohexenones via cyclohexadiene-Fe(CO)3 complexes, to obtain the tetrasubstituted carbon of Aspidosperma-type alkaloids, as demonstrated by the synthesis shown in figure 16 [71]. The iron complexes were also utilized in the synthesis of limaspermine derivatives, as shown in figure 17 [72]. Iron [73] and others metals were also utilized in Aspidosperma alkaloids synthesis, such as rhodium [74–77], copper [75,78], ruthenium and molybdenum [79], titanium [80] and palladium [81,82].
Figure 16.
Synthesis of alkaloids with functionalised C(20) substituents via diene-Fe(CO)3 complex (adapted from [71]).
Figure 17.
Utilization of organoiron chemistry in limaspermine synthesis.
Another precursor of Aspidosperma type alkaloids was synthesized in 1978, from azocetones or iminomalonates via acid-catalysed and Birch reduction reactions (figure 18) [83].
Figure 18.
Synthesis of synthons for Aspidosperma alkaloids synthesis (adapted from [83]).
3.2. Novel strategies
One of the main concerns of chemists worldwide is the development of more efficient and “green” procedures in organic synthesis procedures. Among the procedures developed we can cite the so-called domino synthesis, where several bonds are formed in sequence, without isolation of intermediates, addition of reagents or changes in reaction conditions, so that the subsequent reaction result as a consequence of the functionality formed in the previous step [84]. One example of domino synthesis application to Aspidosperma alkaloids synthesis was recently published, where the alkaloids (-)-aspidospermidine, (-)-tabersonine and (-)-vincadifformine were synthesized in an asymmetric domino Michael/Mannich/N-alkylation sequence, as shown in figure 19 [85].
Figure 19.
Domino Michael/Mannich/N-alkylation sequence to Aspidosperma alkaloids synthesis (adapted from [85]).
The majority of synthetic strategies employed to obtain natural products are based on the construction of a single target skeleton, in contrast with the strategy utilized by plants, where divergent molecular cyclizations of a polyunsaturated common intermediate produce different scaffolds, as recently demonstrated in two different papers, by the synthesis of different Aspidosperma alkaloids[81] and diverse indole alkaloids skeletons [86] from a common intermediate in a biogenetically-inspired way, as shown in figure 20 [86].
Figure 20.
Synthesis of indole alkaloids in a biogenetically-inspired way (adapted from [86]).
4. Biological importance of Aspidosperma terpenoid alkaloids
One of the research interests of our group is the isolation of alkaloids from Aspidosperma species with pharmacological potential. From a chemotaxonomic point of view, alkaloids are substances of great potential in malaria treatment [87,88]. In this perspective, we decided to study the alkaloids produced by A. pyrifolium, resulting in the isolation of the alkaloids 15-demethoxypyrifoline, aspidofractinine and N-formylaspidofractinine [89]. We have identified in A. pyrifolium insecticidal [90], antibacterial [91] and hypotensive activities [92]. Another plant studied by our group was A. tomentosum, which showed great anti-hipertensive [93,94], antinociceptive, anti-inflammatory and analgesic [95–98] and A. macrocarpum, which showed anti-hypertensive activity in spontaneously hypertensive mice [99].
Some species have been the subject of research in order to identify its pharmacological properties and other biological activities. In vitro assay with aqueous extracts of the aerial parts and roots of A. pachypterum against Staphylococcus aureus and the Human Immunodeficiency Virus (HIV), respectively, showed that this species exhibited a moderate activity [100,101]. The methanolic extract of the aerial parts of A. ramiflorum was active in vitro against gram-negative bacterium Escherichia coli [102] and against the fungus Cryptococcus neoformans (causing opportunistic infections in humans) [103] while the methanol extract of the stem bark of the same species was found to be moderately active against gram-positive bacteria and inactive against gram-negatives ones [104]. Studying tailings from the processing of hardwoods in Paraná (Brazil), it was found that the methanol extract of the wood of the plant identified as Peroba pink (Aspidosperma sp.) had a composition rich in phenols and alkaloids as well as strong activity against gram-negative bacteria Proteus mirabilis [105]. In two trials conducted with various plant species, among them five from Aspidosperma genre, it was observed that the ethanol extract of the stem bark of A. excelsum, A. megalocarpon, A. oblongum and A. marcgravianum were active against gram-positive bacteria Bacillus subtilis and that the same extracts and also the ethanol extract of the stem bark of A. album were active against gram-positive S. aureus [106,107]. In a study of Peruvian plants, it was reported that the extract of the bark of A. rigidum showed antibacterial activity against B. subtilis [108].
Another reported activity for species was the anti-Leishmania, where in vitro assay for Leishmania amazonensis promastigotes ahead and L. braziliensis, the fraction rich in alkaloids obtained from the stem bark proved to be active, with the highest activity observed against the first species [109]. Yet in order to find alternatives for the treatment of neglected diseases, the methanol extract of the bark of A. megalocarpon was tested against the D2 and F32 Plasmodium falciparum strains, being active [110]. The dichloromethane extract of the roots of A. tomentosum was active front P. falciparum (strain FcB1/Colombia) with a selectivity index of 67.5 compared with the activity front NIH-3T3 cells. In relation to substances with antifungal properties, it was seen that the ethanol extract of the stem of A. polyneuron was capable of inhibiting Cladosporium herbarum (pathogen of plants) [111].
In order to find alternatives for the treatment of cancer, the dichloromethane extract of the aerial parts of A. tomentosum was capable of inhibiting the proliferation of cell lines MCF-7 (breast cancer), UACC62 (melanoma), NCIADR (breast cancer phenotype with resistance to multiple drugs and NCl460 (lung cancer), and we observed that the activity was concentrated in fractions rich in terpenes and species of high polarity [112].
In vivo assay of the ethanol extract of the stem of A. nitidum showed significant anti-inflammatory activity when evaluated in the trial of edema induced by carrageenan in mice. Prospecting for sources of antioxidant compounds, the hot aqueous extract of A. quebracho-blanco was tested for oxidation power / ferric reduction, showing a low activity and is therefore not considered as potential producer of antioxidant compounds [113].
It was observed that administration of a fraction rich in alkaloids obtained from the root bark of A. ulei exerted pro-erectile effect in rats and suggested a mechanism of action via blocking presynaptic α2-adrenergic receptors, the activation of the dopaminergic system and release of nitric oxide [114]. When the same fraction was tested in corpus cavernosum penis obtained from rabbit, its ability to cause relaxation was observed and the proposed mechanism blocking the influx of calcium into the cells [115]. In assay using α-adrenergic receptors isolated from human penis, it was shown that the crude extract and four fractions obtained from the bark of A. quebracho-blanco were able to block them, and the magnitude of interaction directly proportional to the content of the alkaloid yohimbine [116].
Despite reports of low toxicity associated with the use of plants of the genus Aspidosperma [109,110,117–119], some studies show a contrary position regarding the species A. pyrifolium [89,120]. In a study of the species A. pyrifolium cases of abortion in goats were reported due to ingestion of parts of the plants and when the ethanol extract of the leaves was administered to pregnant rats reduced fetal weight and maternal toxicity was observed, as well as hemolysis and toxicity test the front microcrustacean Artemia salina [120]. In a toxicity study with the microcrustacean A. franciscana with several species found in the Brazilian Amazon, among them seven species of Aspidosperma, it was reported that the bark extracts of A. marcgravianum, A. vargasii, A. nitidum and A. sprucenaum led to mortality of 100, 94, 70 and 65% of the crustaceans, whilst extracts from the bark of A. desmanthum, A. sandwithianum and A. shultesii led to a mortality rate of 6, 0 and 0% crustaceans, showing the potential toxicity of some species gender [121]. In another test with brine shrimp, both the dichloromethane extract and the methanol extract of the bark of A. excelsum showed toxicity [14].
5. Conclusion
The present literature review shows the importance of the study of Aspidosperma type alkaloids due to the widespread usage of plants that produce these substances in folk medicine and the great array of potential biomedical applications that these substances exhibit. Beyond this it is clear the importance of developments in synthetic organic chemistry to obtain these substances without the necessity of extraction from natural sources.
Acknowledgments
We would like to thank the financial support given by CNPq, CAPES, FINEP and FAPEAL agencies.
\n',keywords:null,chapterPDFUrl:"https://cdn.intechopen.com/pdfs/48015.pdf",chapterXML:"https://mts.intechopen.com/source/xml/48015.xml",downloadPdfUrl:"/chapter/pdf-download/48015",previewPdfUrl:"/chapter/pdf-preview/48015",totalDownloads:2202,totalViews:575,totalCrossrefCites:0,totalDimensionsCites:1,totalAltmetricsMentions:0,introChapter:null,impactScore:0,impactScorePercentile:1,impactScoreQuartile:1,hasAltmetrics:0,dateSubmitted:"May 20th 2014",dateReviewed:"October 28th 2014",datePrePublished:null,datePublished:"September 30th 2015",dateFinished:"December 8th 2014",readingETA:"0",abstract:null,reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/48015",risUrl:"/chapter/ris/48015",book:{id:"4528",slug:"phytochemicals-isolation-characterisation-and-role-in-human-health"},signatures:"Pedro Gregório Vieira Aquino, Thiago Mendonça de Aquino,\nMagna Suzana Alexandre-Moreira, Bárbara Viviana de Oliveira\nSantos, Antônio Euzébio Goulart Santana and João Xavier de\nAraújo-Júnior",authors:[{id:"68518",title:"Dr.",name:"João Xavier",middleName:null,surname:"de Araújo-Júnior",fullName:"João Xavier de Araújo-Júnior",slug:"joao-xavier-de-araujo-junior",email:"jotaaraujo2004@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Federal University of Alagoas",institutionURL:null,country:{name:"Brazil"}}},{id:"79536",title:"Dr.",name:"Antônio Euzébio Goulart",middleName:null,surname:"Sant'Ana",fullName:"Antônio Euzébio Goulart Sant'Ana",slug:"antonio-euzebio-goulart-sant'ana",email:"aegs@qui.ufal.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:{name:"Federal University of Alagoas",institutionURL:null,country:{name:"Brazil"}}},{id:"172038",title:"MSc.",name:"Pedro",middleName:null,surname:"Aquino",fullName:"Pedro Aquino",slug:"pedro-aquino",email:"pgvaquino@qui.ufal.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"172039",title:"Dr.",name:"Thiago Mendonça",middleName:null,surname:"De Aquino",fullName:"Thiago Mendonça De Aquino",slug:"thiago-mendonca-de-aquino",email:"thiago.wanick@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"174306",title:"Prof.",name:"Barbara",middleName:null,surname:"Santos",fullName:"Barbara Santos",slug:"barbara-santos",email:"barbara@ltf.ufpb.br",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null},{id:"174307",title:"Prof.",name:"Magna Suzana",middleName:null,surname:"Alexandre-Moreira",fullName:"Magna Suzana Alexandre-Moreira",slug:"magna-suzana-alexandre-moreira",email:"suzana.magna@gmail.com",position:null,profilePictureURL:"//cdnintech.com/web/frontend/www/assets/author.svg",institution:null}],sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. Biosynthesis of Aspidosperma terpenoid alkaloids",level:"1"},{id:"sec_3",title:"3. Chemical synthesis of Aspidosperma terpenoid alkaloids",level:"1"},{id:"sec_3_2",title:"3.1. Aspidosperma alkaloid precursors",level:"2"},{id:"sec_4_2",title:"3.2. Novel strategies",level:"2"},{id:"sec_6",title:"4. Biological importance of Aspidosperma terpenoid alkaloids",level:"1"},{id:"sec_7",title:"5. Conclusion",level:"1"},{id:"sec_8",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Newman DJ, Cragg GM, Snader KM. The influence of natural products upon drug discovery. Natural Products Report 2000;17:215–34.'},{id:"B2",body:'Kinghorn AD. Drug discovery form natural products. In: Lemke TL, Williams DA, Roche VF, Zito SW, editors. Foye’s Principles of Medicinal Chemistry 6th ed., Philadelphia: Lippincott Williams & Wilkins; 2008, p. 12–25.'},{id:"B3",body:'De Pasquale A. Pharmacognosy: the oldest modern science. 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In vitro anti-HIV and antitumor evaluation of Amazonian plants belonging to the Apocynaceae family. Phytomedicine 2002;9:175.'},{id:"B101",body:'Suffredini IB, Bacchi EM, Mary T, Sakuda K, Ohara MT, Younes RN, et al. Antibacterial activity of Apocynaceae extracts and MIC of Tabernaemontana angulata stem organic extract. Revista Brasileira de Ciências Farmacêuticas 2002;38:89–94.'},{id:"B102",body:'Agripino DG, Leite EML, da Silva RM, Meda CI, Bolzani V da S, Cordeiro I, et al. Screening of brazilian plants for antimicrobial and DNA-damaging activities. I. Atlantic rain forest-Ecological station Juréia-Itatins. Biota Neotropica 2004;4:1–15.'},{id:"B103",body:'De Souza ACM, Hasimoto e Souza LK, Silva MRR, Oliveira CMA, Kato L, da Silva CC, et al. Propriedades antifúngicas dos alcalóides de Aspidosperma ramiflorum. 29a Reun. Anu. da Soc. Bras. Química, vol. 46, Águas de Lindóia: 2006.'},{id:"B104",body:'Tanaka JCA, da Silva CC, de Oliveira AJB, Nakamura C V, Dias Filho BP. Antibacterial activity of indole alkaloids from Aspidosperma ramiflorum. Brazilian Journal of Medicine and Biological Research 2006;39:387–91.'},{id:"B105",body:'Granato D, Nunes DS, Mattos PP De, Moura E De, Samples W. Chemical and Biological Evaluation of Rejects from the Wood Industry Microbiological activity of the extracts. Brazilian Archives of Biology and Thecnology 2005;48:237–41.'},{id:"B106",body:'Verpoorte R, Tsoi ATA, Doorne HVAN, Svendsen AB. Medicinal plants of Suriname. I. Antimicrobial activity of some medicinal plants. Journal of Ethnopharmacology 1982;5:221–6.'},{id:"B107",body:'Verpoorte R, Van Beek TA, Thomassen PHAM, Aandewiel J, Svendsen AB. Screening of antimicrobial activity of some plants belonging to the Apocynaceae and Loganiaceae. Journal of Ethnopharmacology 1983;8:287–302.'},{id:"B108",body:'Rojas R, Bustamante B, Bauer J, Fernández I, Albán J, Lock O. Antimicrobial activity of selected Peruvian medicinal plants. Journal of Ethnopharmacology 2003;88:199–204.'},{id:"B109",body:'Ferreira ICP, Lonardoni MVC, Machado GMC, Leon LL, Gobbi Filho L, Pinto LHB, et al. Anti-leishmanial activity of alkaloidal extract from Aspidosperma ramiflorum. Memórias do Instituto Oswaldo Cruz 2004;99:325–7.'},{id:"B110",body:'Weniger B, Robledo S, Arango GJ, Deharo E, Aragón R, Muñoz V, et al. Antiprotozoal activities of Colombian plants. Journal of Ethnopharmacology 2001;78:193–200.'},{id:"B111",body:'Ferreira DT, da Silva Jr. J V, Soeira LS, Zanolli LA, Ishikawa NK, Barbosa AM, et al. Avaliação da atividade antifúngica dos extratos etanólicos de raiz, caule e folha de Aspidosperma polyneuron. An. do XI Encontro Química da Região Sul, 2003, p. QO83.'},{id:"B112",body:'Kohn LK, Pizão PE, Foglio MA, Antônio MA, Amaral MCE, Bittric V, et al. Antiproliferative activity of crude extract and fractions obtained from Aspidosperma tomentosum Mart. Revista Brasileira de Plantas Medicinais Botucatu 2006;8:110–5.'},{id:"B113",body:'Borneo R, León a. E, Aguirre a., Ribotta P, Cantero JJ. Antioxidant capacity of medicinal plants from the Province of Córdoba (Argentina) and their in vitro testing in a model food system. Food Chemistry 2009;112:664–70.'},{id:"B114",body:'Campos AR, Lima RCP, Uchoa DE a, Silveira ER, Santos F a, Rao VSN. Pro-erectile effects of an alkaloidal rich fraction from Aspidosperma ulei root bark in mice. Journal of Ethnopharmacology 2006;104:240–4.'},{id:"B115",body:'Campos a R, Cunha KM a, Santos F a, Silveira ER, Uchoa DE a, Nascimento NRF, et al. Relaxant effects of an alkaloid-rich fraction from Aspidosperma ulei root bark on isolated rabbit corpus cavernosum. International Journal of Impotency Research 2008;20:255–63.'},{id:"B116",body:'Sperling H, Lorenz A, Krege S, Arndt R, Michel MC. An extract from the bark of Aspidosperma quebracho blanco binds to human penile alpha-adrenoceptors. Journal fo Urology 2002;168:160–3.'},{id:"B117",body:'Goloni R, Alves NM, Garrote CFD, Paula JR, Valadares MC, Bara MTF, et al. Estudo da toxicidade aguda do Aspidosperma subincanum Martius. Revista Eletrônica de Farmácia 2005;2:89–91.'},{id:"B118",body:'Pereira MDM, Jácome RLRP, Alcântara AFC, Alves RB, Raslan DS. Alcaloides indólicos isolados de espécies do gênero Aspidosperma (APOCYNACEAE). Quimica Nova 2007;30:970–83.'},{id:"B119",body:'Santos SR, Rangel ET, Lima JCS, Silva RM, Lopes L, Noldin VF, et al. Toxicological and phytochemical studies of Aspidosperma subincanum Mart. stem bark (Guatambu). Pharmazie 2009;64:836–9.'},{id:"B120",body:'De Souza Lima MCJ, Soto-Blanco B. Poisoning in goats by Aspidosperma pyrifolium Mart.: biological and cytotoxic effects. Toxicon 2010;55:320–4.'},{id:"B121",body:'Quignard ELJ, Pohlit AM, Nunomura SM, da Silva Pinto AC, dos Santos EVM, de Morais SKR, et al. Screening of plants found in amazonas state for lethality towards brine shrimp. Acta Amazonica 2003;33:93–104.'}],footnotes:[],contributors:[{corresp:null,contributorFullName:"Pedro Gregório Vieira Aquino",address:null,affiliation:'
Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, Brazil
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Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, Brazil
Institute of Chemistry and Biotechnology, Federal University of Alagoas, Maceió, Brazil
'},{corresp:"yes",contributorFullName:"João Xavier de Araújo-Júnior",address:"jotaaraujo2004@gmail.com",affiliation:'
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1. Introduction
“Once one starts to think about the human welfare consequences of economic growth, it is hard to think about anything else” [1]. Economic growth is the basis for increased prosperity, and its importance cannot be overstated. Barro and Sala-i-Martin [2] argue that continuous and sustained economic growth is important for improving the welfare of individuals and that aggregate growth is probably the single most important factor affecting individual levels of income. Due to the importance of economic growth, attainment of high economic growth rates is a major national objective of any country. It is, however, puzzling and at the same time worrisome that the riches of the world are so unequally shared among countries [3].
Over the years, growth performance has varied notably across regions and countries. In some economies, it has experienced major shifts over time. A few developing countries have experienced rapid growth yet some other countries have grown at only a stagnant rate. This discrepancy in economic growth among numerous countries and the dynamics of growth have become provocative research targets. The main questions are why some countries are rich while others are poor, and what determines the rate of growth? Rosa notes that it seems certain that there is no all-encompassing theory of economic growth, but different sources of economic growth can be observed to be relevant for different stages of economic development.
Several reasons have been provided that explain the differences, key among them being the fact that initial conditions differ greatly. Isaksson [4] asserts that some, if not many, of the differences in income per capita are human-created. He asserts that how a society and its production are organized can significantly explain the observed income divergence since the industrial revolution.
In the case of Uganda, the last five decades have been difficult in terms of overall economic growth and stability, let alone the first eight years after independence and the last three decades, when episodes of high yet unstable economic growth occurred, especially from the late 1980s to the late 2000s. Economic growth was impressive for the first eight years after independence, but by 1986, the economy had descended into a deep recession owing to poor governance from the early 1970s to that time. Since 1986, the country has undergone a major transformation from a “failed state” to one of the fastest-growing economies in the world. As early as 1993, Uganda started implementing structural adjustment programmes (SAPS) and other economic policies and programmes such as; economic recovery programme (ERP), medium-term expenditure framework, Plan for Modernization of Agriculture (PMA), and Poverty Eradication Action Plan (PEAP), among others all aimed at poverty reduction and attaining higher levels of economic growth in Uganda. The reforms ushered in relatively high economic growth rates based on incentives for private production. Between 1990 and 2010, GDP growth averaged 7.3 percent per annum, placing Uganda among the fastest-growing economies in the world and creating momentum for take-off. This growth was higher than the Sub-Saharan African growth rate, which averaged approximately 2.1 and was close to that of the East Asian and Pacific region of 7.9 and 6.6 percent, respectively.
To consolidate and accelerate this growth process, the Ugandan government approved the Comprehensive National Development Planning Framework Policy in 2007 which provided the developmental agenda for a 30-year vision to be implemented through three 10-year plans and six 5-year national development plans (NDPs), among other operational plans. However, data shows that Uganda’s growth has been mostly unstable; it has been described as unsustainable because it has been sustained partly by significant aid inflows and only a few tradable commodities, such as coffee, flowers and fish. The government of Uganda, like many other governments elsewhere continues to target improving GDP growth. The key to achieving this improvement has been the careful development and implementation of policies and programmes to improve capital stock, labour stock, price stability and productivity and competitiveness as major drivers of economic growth [5].
Uganda has set its Vision 2040 as a guiding framework for transforming the country from “a peasant to a modern and prosperous country with a per capita income of USD 9,500 from the base figure of USD 506 in the year 2010 by the year 2040”. For the country to achieve this transformation, Uganda Vision 2040 projects that Uganda’s real GDP will have to grow at an average of 8.2 percent, while the IMF forecasts approximately 9 percent growth rate as necessary for the remaining period. However, the achievement of Vision 2040 has been threatened not only by lower-than-targeted rates of annual GDP growth since the inception of the vision but also by a recent slump from the average GDP growth rate of approximately 6.8 percent that was posted in the last half of the 2000s to an average of 4.6 percent between 2010 and 2015.
To achieve the Vision, understanding the determinants of past growth, removing the constraints on present growth and maximizing the prospects for future growth are key. It is important to note that inferring the determinants of growth faces considerable uncertainty due to the existence of multiple overlapping theories that emphasize different channels of growth over time. Therefore, this paper aims at providing more robust and targeted policy interventions to generate higher and more sustainable economic growth by examining the determinants of economic growth in Uganda using the ARDL frameworks.
2. A review of empirical literature
A wide range of studies have investigated the factors underlying economic growth in different countries. Using differing conceptual and methodological viewpoints, studies have identified different factors that explain economic growth world over [6]. However, existing literature has not yet reached a consensus about a typical set of variables that may affect economic growth.
The accumulation of physical capital (investment) is one of the most fundamental determinants of economic growth identified in the literature per the neoclassical and endogenous growth models and much empirical work has been performed on the subject [7, 8, 9]. It has been found to be robust to most specifications and sample size changes [10]. The impact of several types of investment has been studied over time and varying levels of significance have been attached to varying types of investment. Gross capital formation affects economic growth by either directly increasing the physical capital stock in the domestic economy [11] or indirectly promoting technology [12]. Other researchers have investigated the impact of private and public investment on economic growth and have found significant variations. Khan and Kumar [13] found private investment to be more productive than public investment. In this paper, investment is represented by physical capital accumulation and it is expected to have a positive and statistically significant relationship with economic growth.
Exports are another factor identified by both the neoclassical and endogenous growth models in explaining economic growth variations. Awokuse [14] notes that linking exports to economic growth is pied when he found that there is a flow of Granger cause from real exports to real GDP. There is also a strand of studies that find no conclusive evidence of the causal relationship between exports and GDP growth. Ruiz-Nápoles [15] argues that even in cases where increasing exports has a positive effect on production expansion, such an effect may be limited and offset by increasing manufacturing imports displacing domestic production. Fouad Abou-Stait [16] found that time series studies find fewer conclusive associations between exports and growth, whereas cross-sectional studies appear to support the positive relationship.
Closely related to exports is trade openness with mixed results. A large part of the literature find that economies that are more open grow more rapidly [17, 18, 19, 20]. Baliamoune [21] finds that trade openness is closely associated with positive effects in higher-income and negative effects in lower-income African countries. Arezki and Gylfason [22] find that trade openness has a positive and statistically significant impact on non-resource GDP growth. Several scholars have however criticized the robustness of these findings, especially on methodological and measurement grounds (see, [23, 24]). Vamvakidis [24] and Wong [25] find a negative relationship between openness to international trade and economic growth. Fowe finds no significant effect of openness to trade on economic growth in SSA.
Several endogenous growth models and extensions of the neoclassical growth model find human capital and/or knowledge to be a major source of growth [26]. A large number of studies find evidence suggesting that an educated population is a key determinant of economic growth (see [8, 27, 28]). However, other scholars find mixed results while others question studies that have found a positive relationships [29, 30]. Some empirical findings have shown that human capital accumulation plays only a small role in economic growth [31]. Studies by Bils and Klenow [32], Pritchett [29], Easterly and Levine [33] found that the evidence was weak, absent or even pointed to a negative impact.
Population growth rate is another important variable in economic growth literature. The relationship between population and economic growth is mixed and varies between countries [34]. Some empirical studies have found a negative relationship between population and economic growth [35, 36]; and in others there was a positive association with economic growth [37, 38]. Another factor influencing economic growth is population growth rate [36, 39, 40]. High population growth, for example, could have a negative impact on economic growth, influencing the dependency ratio, investment and saving behavior and quality of human capital countries [41]. However, the findings are again inconclusive since there some studies have reported no (strong) correlation between economic growth and demographic trends (e.g., [29, 42]).
Foreign Aid has received renewed political interest in economic growth discourse resulting into numerous studies. There is however little evidence of a significant positive effect of aid on the long-term growth of poor countries [43, 44]. Andersson and Karlsson, C. [45] finds support for the basic idea that an increase in aid flows strengthens economic growth in poor countries when the policy environment is conducive. Collier and Dehn [46] find that well-timed aid alleviates effects of negative export shocks while Collier and Hoeffler [47] find that aid works particularly well in good policy environments a few years after a conflict has ended. Other scholars argue that aid spurs economic growth unconditionally (see, [37, 48]), or in certain macroeconomic environments that it is growth-neutral [49]. In contrast, some studies have argued that aid has historically been ineffective in promoting growth [50, 51]. Rajan and Subramanian [43] provide evidence that total aid is ineffective at promoting growth.
The relationship between government consumption expenditure and economic growth has attracted a great deal of interest among policymakers and economists. Empirical work on this subject has also provided mixed results. On one side, there are Keynesian economists who consider consumption expenditure as a dependable function of income and on the other side there are substantial numbers of economists who believe that higher consumption can stimulate economic growth [52, 53]. Other studies have found that small to moderate government sizes are positively associated with economic growth while large government sizes impede economic growth [54, 55].
It is argued that inflation is a good macroeconomic indicator of how the government manages the economy [55, 56, 57]. Although the empirical evidence has strongly supported a negative relationship between inflation and growth, especially through the impact of inflation on capital intensity [58], other studies have found that inflation exhibits threshold effects on economic growth [59, 60]. Khan and Senhadji, [60] explore this issue and reach several conclusions. In particular, medium and high inflation hamper economic growth due to the adverse impact on the efficient distribution of resources by changing relative prices [57].
3. Analytical framework and data
3.1 Theoretical framework
Based on the foregoing literature, we assume a Cobb–Douglas production function with labour-augmenting (Harrod-Neutral) technological progress following Mankiw, et al. [27] and Acikgoz and Mert [61].
Y=KαALβ;<α,β<1Such thatα+β=1E1
where Y, K and L indicate the levels of output, capital stock and, labour respectively, and A indicates the level of technology. But Economists have long stressed the importance of human capital to the process of economic growth. Following Mankiw, et al. [27], the augmented classic Solow model takes the following form:
Yt=Kt∝HCtβAtLt1−∝−βE2
where HC is human capital, and all other variables are defined as before. Following Mankiw, et al. [27], Acikgoz and Mert [61], and Chirwa and Odhiambo [17], the aggregate Cobb–Douglas production function is assumed to take the following form:
Yt=Kt∝HCtβAtGCtAIDtINFt,TRDtLt1−∝−βE3
where α and β represent the partial elasticity of output with respect to physical capital and human capital respectively. Per the literature, technological progress (At) is assumed to be labour augmenting and the function therefore denotes a skill-adjusted measure of the labour input.
Several efficiency variables have been identified in the literature to provide a link to how policy variables influence the aggregate production function [55, 57]. The variables selected for this study consist of the accumulation of physical capital (investment); human capital (total school enrolment); population; and policy variables (efficiency factors) that include government consumption share in GDP, inflation, foreign aid as a share of GDP and international trade. The efficiency factors, similar to population growth, are assumed to grow exogenously (see [27, 62]).
3.2 Estimation techniques
Auto Regressive Distributed Lag (ARDL) bounds testing approach developed by Pesaran and Shin [63], Pesaran, Shin and Smith [64] was employed. The modeling approach allows us to capture the short and long run dynamics as well as the speed of adjustment between the independent variables and the dependent variable. The embedded Error Correlation Model (ECM) is a restricted representation that has cointegration restrictions built into the specification so that it is designed for use with non-stationary series that are known to be cointegrated. The ECM specification restricts the long run behavior of the endogenous variables to converge to their cointegrating relationships while allowing a wide range of short run dynamics. Choice of the ARDL model was taken based on the following reasons: (1) the variables were found to be integrated of different orders i.e. (I(0) and I(1) and ARDL can be applied even when variables are not integrated of the same order; (2) ARDL performs better than other co-integration tests in small and finite data samples [65]. The two stage ARDL approach effectively corrects for any possible endogeneity in the regressors [61, 66]; (3) According to [67, 68] the ARDL model also allows for different optimal lags among the different variables to capture the data-generating process as a general-to-specific modeling framework [68, 69], (4) ARDL is known to have information about the structural break in time series data and lastly Pesaran and Shin [63] contented that appropriate modification of the orders of the ARDL model is sufficient to simultaneously correct for residual serial correlation and the problem of endogenous variables. The only drawback being that ARDI approach collapses when variables are integrated of order two (i.e I(2)).
The ARDL representation of the empirical model for this study is expressed as follows:
where ∆ is the difference operator, α0 is the drift component, p is the lag length, α1i is the short-run coefficient and β1i is the corresponding long-run multiplier and εit is the white-noise error term of the underlying ARDL model.
Two steps are involved in estimating an ARDL model. First, the long-run equilibrium relationship between the variables is tested using the upper and lower bounds; then, the short-run and long-run causalities are estimated. The ARDL bounds test is based mainly on the joint F-statistic in which its asymptotic distribution is non-standard under the null hypothesis of no co-integration [70].
In Eq. 4 above, the null hypothesis of no co-integration relationship, defined as H0:Ø1=Ø2=Ø3=Ø4=Ø5=Ø6=Ø7=Ø8=0, is tested against the alternative of the existence of a co-integration relationship as H1: Ø1≠Ø2≠Ø3≠Ø4≠Ø5≠Ø6≠Ø7≠Ø8≠0for i=1,2,3,4,5,6,7,8. The hypothesis is tested using the mean of the computed F-statistic. According to Pesaran et al. [64], given that the model takes the form of ARDL (p, q), two sets of critical values for a given significance level are then determined because p and q need not be integrated of the same order.
Using the Wald test, the computed F-statistic is then compared with the lower and upper asymptotic critical bounds values, as reported in Pesaran et al. [64]. The lower-bound critical value assumes that all the regressors are l(0), while the upper-bound critical value assumes that they are I(l). We reject the null hypothesis of no co-integration if the computed test statistic exceeds the upper-bound critical value, and we do not reject the null hypothesis if the F-statistic is lower than the lower-bound critical value. The test is, however, inconclusive if the computed F-statistic lies between the lower-bound and upper-bound critical values. In this context, unit root tests should be conducted to ascertain the order of integration of the variables. If all the variables are found to be I(1), then the decision is made on the basis of the upper-bound critical value. On the other hand, if all the variables are I(0), then the decision is based on the lower-bound critical value. To test for the long-run relationship between the variables, we exclude the lagged-level variables from Eq. (4). Once the presence of co-integration is confirmed, we estimate the long-run coefficients of the growth model and the associated ARDL of the ECM for the short-run coefficients.
The ARDL method estimates (p + 1)k number of regressions to obtain the optimal lags for each variable, where p is the maximum number of lags to be used and k is the number of variables in the equation [71]. The model is selected based on the Schwartz-Bayesian criterion (SBC) or the Akaike information criterion (AIC).
3.2.1 Estimation of the error correction-based ARDL model
ARDL estimation provides both the short run (model) and long run estimation results. The ECM is specified as follows:
where β9i is the coefficient of the one-lag error correction model, which measures the short-run speed of adjustment to restore equilibrium in the dynamic model following a disturbance [72]. This implies that the coefficient of the error correction should be negative and statistically significant and that the magnitude of this coefficient should be less than one.
3.3 Data type and sources
Annual time series data for the period 1982–2015, that was obtained from World Bank Development Indicators [73, 74] was used in this study. The following variables were used: Real GDP (expressed in 2010 U.S. dollars.) at purchaser’s prices; Investment (proxied by gross fixed capital formation as a share of GDP); Inflation (measured by the consumer price index); General government expenditure as a share in GDP (General government expenditure as a share in GDP); Human Capital (representing knowledge spill over effects) was proxied by Human capital index3, based on years of schooling and returns to education); Demography (proxied by total population); Trade openness (measured by the sum of exports and imports as a proportion of GDP); and Foreign Aid as a proportion to GDP (measured by net official development assistance and official aid received as a share of real GDP). Eviews 9.5 software was used to conduct the empirical analysis.
3.4 Analysis and discussion of results
3.4.1 Unit root tests
Unit roots/stationarity tests were conducted because this is a prime requirement for any co-integration and causality tests. The augmented Dickey-Fuller test (ADF: [75]) was used to establish the order of integration. The ADF test results were augmented with the Phillips-Perron (PP: [76]) test. Table 1 presents the results of the unit root tests.
Variables
Augmented Dickey Fuller
Phillips-Perron test
Constant + trend
Constant + trend
Part A: Level
Log Real Gross Domestic Product
−3.48*
−3.48*
Log Trade Openness
−2.81
−2.62
Log Human Capital
−2.84
−2.26
Log Population Growth
−0.06
−1.72
Log Gross Government Final Consumption (% GDP)
−1.77
−1.71
Log Gross Fixed Capital Formation
−3.95**
−2.89
Log Inflation Rate
−5.28***
−2.22
Log Aid
−2.24
−2.18
Log Total School Enrolment, Primary
−1.85
−1.74
Log Imports
3.41*
−2.43
Log Exports
−2.86
−3.21
Part B: First difference
Log Real Gross Domestic Product
−3.38*
−3.38*
Log Trade Openness
−4.51***
−4.37***
Log Human Capital
−3.80
−3.85*
Log Population Growth
−3.80**
−2.35
Log Gross Government Final Consumption (percent) GDP)
−4.92***
−6.02***
Log Gross Fixed Capital Formation
−4.33***
−5.24***
Log Inflation Rate
−2.05
−2.30
Log Aid
−6.41***
−7.56***
Log Total School Enrolment, Primary
−6.91***
7.08***
Log Imports
−3.77**
−3.40*
Log Exports
−6.49***
−6.49***
Table 1.
Unit root test at level and in first difference.
***, **, and * denote rejection of the null hypothesis of unit root at the 1 percent, 5 percent and 10 percent significance levels, respectively.
The ADF test results with trend and intercept at level in part A indicate that GDP, GGC, and GFCF were stationary at the 5 percent level of significance, whereas CPI was stationary at the 1 percent level of significance. The researcher thus carried out stationarity tests for all series in first difference with constant and trend, as indicated in part B (ADF test), and the variables, except CPI, became stationary.
The variables were also tested for stationarity using the Phillips-Perron test. The PP test results at level with constant and trend were found to be non-stationary except for GDP and GGC, which were found to be stationary at 10 percent and 5 percent levels of significance, respectively. The variables were tested for stationarity in first difference, and they all became stationary except CPI.
3.4.2 ARDL bounds tests for co-integration results
We tested for co-integration among the variables to establish whether they had a long-run relationship. From a statistical point of view, a long-run relationship implies that variables move together over time and that short-term disturbances arising from the long-term trend are corrected. Co-integration is necessary because a valid ARDL requires the presence of a co-integrating set of variables. The ARDL method allows us to test both short- and long-run relationships between the dependent and independent variables in a multivariate framework. The critical value bounds are computed by stochastic simulations using 20,000 replications [66].
The variables are jointly tested if they are equal to zero. That is:
H0: They are jointly equal to zero.
H1: They are not jointly equal to zero.
Once the test statistic is computed, it is compared to two asymptotic critical values corresponding to polar cases of all variables being purely I(0) or purely I(1). When the test statistic is below the lower-bound critical value, the null hypothesis is not rejected, and co-integration is not possible. In contrast, when the test statistic is above the upper-bound critical value, the null hypothesis is rejected, and co-integration is indeed possible. Alternatively, should the test statistic fall between the lower-bound and upper-bound critical values, the test results are inconclusive, and knowledge of the co-integration rank is required to proceed further.
The Akaike information criterion was employed to determine the appropriate lag length for the estimated ARDL equation. This method was chosen because it tends to over-fit the model of interest, given that the optimal lag length for the growth model is up to 2 lags. The optimal lag length is chosen based on the number of dynamic regressors included in the model and the sample size. The optimal lag-length selection criteria are based on the lowest AIC obtained. For this growth equation, (regression I), the optimal ARDL model selected was the ARDL (2, 1, 0, 1, 0, 1, 0, 0, 2) model with restricted intercept and trend, while for regression II, the optimal ARDL model selected was the ARDL (2, 0, 2, 0, 1, 0, 0, 1, 0, 2) model with restricted intercept and trend. Table 2 reports the Pesaran et al. [64] bounds test for level relationships for the selected equation.
ARDL bounds test
Regression I
Regression II
Included observations: 32 after adjustments
Null hypothesis: no long-run relationships exist
Test statistic
Value
k
Value
K
F-statistic
5.47***
8
3.909**
9
Critical Value Bounds
Significance
I0 Bound
I1 Bound
I0 Bound
I1 Bound
10 percent
1.95
3.06
1.88
2.99
5 percent
2.22
3.39
2.14
3.3
2.5 percent
2.48
3.7
2.37
3.6
1 percent
2.79
4.1
2.65
3.97
R-squared
0.845152
0.852168
Adjusted R-squared
0.699981
0.672657
Table 2.
Results of ARDL bounds test for co-integration.
***, **, and * denote 1 percent, 5 percent and 10 percent significance levels, respectively.
As illustrated in Table 2, regression I, the computed 𝐹-statistic is 5.47, and it is statistically significant at the 1 percent upper-bound critical value, meaning that the null hypothesis of no co-integration is rejected at the 1 percent significance level. In regression II, the computed 𝐹-statistic is 3.909, and it is statistically significant at the 5 percent upper-bound critical value, meaning that the null hypothesis of no co-integration is rejected at the 5 percent significance level. In summary, the bounds test of co-integration relationships using the Pesaran et al. [64] approach confirms the existence of long-run level relationships between the dependent variable and the set of covariates in both regressions. The study results also reveal that the underlying ARDL model is a good fit, represented by an estimated R−squared value of 0.84 and an adjusted R−squared value of 0.67.
3.4.3 Relative superiority of the selected models
Using the ARDL model, the researcher selected the overall best model from the 20 best selected ARDL models. As shown in Figure 1, the selected model in regression I is ARDL (2, 1, 0, 1, 0, 0, 1, 0, 0, 2), and the selected model in the second regression is ARDL (2, 0, 2, 0, 1, 0, 0, 1, 0, 2). These two models were significantly superior to the second-best models in each case [66].
Figure 1.
Relative superiority of the selected models.
3.4.4 Empirical results of the ARDL models
The short and long run elasticities for the ARDL model were estimated. Table 3, part A presents the short-run ARDL results (including the ECM representation), while part B pre-sets the long-run results of the ARDL models.
ARDL co-integration and long-run form
Dependent variable: LRGDP
Part A
Co-integration form
Selected Model: Included observations: 32
ARDL (2,1,0,1,0,1,0,0,2)
ARDL (2,0,2,0,1,0,0,1,0,2)
Co-integration Form
Regression I
Regression II
Variable
Coefficient(Prob.)
Coefficient (Prob.)
D(Log Real Gross Domestic Product (−1))
0.179(0.049)**
0.279(0.003)***
D(Log Trade Openness)
0.036(0.190)
D(Log Population Growth)
0.481(0.784)
0.126(0.941)
D(Log Inflation Rate)
−0.085(0.000)**
−0.086(0.000)*
D(Log Human Capital)
0.240(0.507)
0.619(0.109)
D(Log Gross Government Consumption)
0.061(0.001)***
0.066(0.000)***
D(Log Gross Fixed Capital Formation)
0.192(0.000)***
0.145(0.000)***
D(Log Aid)
−0.033(0.022)**
−0.021(0.111)
D(Log Exports)
0.027(0.047)**
D(Log Imports)
0.056(0.178)
D(Dummy for Structural Adjustment)
−0.008(0.092)*
−0.018(0.007)***
C
0.185(0.001)***
2.786(0.000)***
Coint Eq (−1)
−0.595(0.00)***
−0.646 (0.000)***
PART B
Long-Run Coefficients
Variable
Coefficient
Log Trade Openness
0.295(0.002)***
Log Population Growth
1.008(0.090)*
0.334(0.605)
Log Inflation Rate
−0.009(0.624)
−0.018(0.361)
Log Human Capital
0.293(0.639)
0.848(0.244)
Log Gross Government Consumption (percent, GDP)
0.198(0.001)***
0.159(0.007)***
Log Gross Fixed Capital Formation
0.316(0.003)***
0.220(0.029)**
Log Aid
−0.053(0.227)
−0.032(0.399)
Log Exports
0.121(0.007)***
Log Imports
0.090(0.244)
D(Dummy for Structural Adjustment)
−0.007(0.003)***
−0.071(0.003)***
Table 3.
Short-run and long-run ARDL results.
***, **, and * denote 1 percent, 5 percent and 10 percent significance levels, respectively.
Part A of Table 3 reports the estimated short-run coefficients, while Part B reports the estimated long-run coefficients. Two different regressions were estimated. Regression I was the “benchmark” regression, while regression II was used for sensitivity/options analysis. Among other variables, regression II used a different proxy for trade openness, which is a fundamental variable for GDP growth, according to the literature. Specifically, instead of using trade openness, we used exports and imports to examine the effect of trade on GDP growth.
As shown in part A, the short-run dynamics and the adjustment towards the long-run equilibrium path are measured by the error correction term (ECT) [77]. In the short run, deviations from the long-run equilibrium can occur due to shocks in any of the variables in the model; thus, all the short-run coefficients show the dynamic adjustments of all variables to their long-run equilibrium [70]. If the coefficient is significant, it implies that past equilibrium errors play a role in determining the outcomes of the current period. The ECT measures the speed of adjustment to restore equilibrium in the dynamic model after a disturbance. For the coefficient to be significant, it is required that the error correction term (ECT) must be negative and significant. A highly significant ECT is further proof of a stable long-run relationship [78].
From Table 3, part A, regression I, the ECT estimation results show that the estimated coefficient of the error correction term has the expected sign (negative) and is statistically significant. This reinforces the finding of a long-run relationship in the co-integration equation. The results show that a 1 percent deviation from the equilibrium path is corrected in the next period at a rate of 59.5 percent and is statistically significant at the 1 percent significance level. This confirms the presence of a long-run level equilibrium path between real GDP and the selected regressors (trade openness, human capital, population, government consumption, investment, inflation, foreign aid and a policy dummy (structural adjustment programme). The regression results for the ARDL model reveal a good fit represented by an estimated R-squared value of 0.85 and an adjusted R-squared value of 0.70, as shown in Table 3.
Part B, regression I of Table 3 presents the long-run coefficient estimates. The results reveal that the key macroeconomic determinants that are significantly associated with long-run economic growth in Uganda include trade openness, population growth, government consumption, investment, and the policy dummy variable for the structural adjustment programmes (SAPs).
In the long run, the relationship between trade openness and real GDP is positive and statistically significant at the 1 percent significance level. The results reveal that a 1 percent increase in trade openness in the long run leads to a 0.295 percent increase in the level of real GDP. These findings are supported by previous studies that have found a positive and significant relationship between trade openness and economic growth (e.g. [17, 19, 20]).
The study reveals that population growth is positively and significantly associated with the growth of real GDP in Uganda at the 10 percent level of significance. It shows that a 1 percent increase in population leads to a 1.01 percent increase in real GDP. These results are supported by similar studies conducted in developing countries that have found a positive relationship between investment and economic growth in the long run (e.g., [41, 79]).
The study reveals a positive relationship between government consumption and the growth of real GDP at the 1 percent significance level in the long run. A 1 percent increase in government consumption results in a 0.20 percent increase in the level of real GDP. These results are supported by similar studies conducted in developing countries that have found a positive relationship between government consumption and economic growth in the long run (e.g., [17]).
The results confirm the widely established empirical estimation finding that investment and growth in GDP have a positive relationship. A 1 percent increase in the level of investment results in a 0.32 percent increase in the level of real GDP. These results are supported by similar studies conducted in developing countries that have found a positive relationship between investment and economic growth in the long run (e.g., [10, 54, 80, 81, 82]).
The study results did not reveal a significant association between inflation, human capital and foreign aid and the long-run level of GDP growth.
The short-run results presented in Part A of Table 3 reveal that the key macroeconomic determinants that are significantly associated with the growth of real GDP in the short run are initial GDP, inflation, government consumption (percent of GDP), investment, foreign aid, and the policy dummy. The results show that a 1 percent increase in initial real GDP leads to a 0.18 percent increase in real GDP. Meaning that the level of and sign of initial GDP has a positive relationship with current GDP.
The results reveal a negative association between inflation and economic growth. A 1 percent increase in inflation leads to a 0.90 reduction in GDP. These results are supported by a number of empirical growth studies that have also found a negative association between inflation and economic growth in developing countries (e.g., [56, 57, 83, 84, 85, 86]).
The results show that government consumption is positively and significantly associated with the growth of real GDP at the 1 percent significance level. A 1 percent change in government consumption leads to a 0.06 percent increase in the growth of GDP. The positive relationship found between government consumption and economic growth is supported by similar studies in the empirical growth literature that have found a positive relationship between trade openness and economic growth (e.g., [17, 87]).
There is a positive and significant relationship between investment and economic growth at the 1 percent level of significance. A 1 percent increase in investment leads to a 0.19 percent increase in GDP. The results are consistent with existing empirical growth studies that have found a positive relationship between investment and economic growth (e.g., [10, 17, 88]).
The results show that foreign aid is negatively and significantly associated with the growth of real GDP, and the results are statistically significant at the 5 percent significance level. A 1 percent change in foreign aid leads to a 0.03 percent reduction in the growth of GDP. The negative relationship found between foreign aid and economic growth is supported by similar studies in the empirical growth literature (e.g., [10]).
The study results did not reveal a significant association between trade openness, population growth, human capital, and real GDP growth in the short run.
Sensitivity analysis was carried out to examine the significance of other variables or proxies for the variables used in regression II. This analysis was carried out bearing in mind theory, certain empirical studies and the nature of the Ugandan economy. Key variables/proxies were imports and exports as proxies for trade openness. Exports were found to be positively and significantly associated with GDP at the 1 percent level of significance, while imports were found to be non-significant.
From Table 3, Part A, regression II above, the ECT estimation results show that the estimated coefficient of the error correction term has the expected sign (negative) and is statistically significant. The ECT shows that a 1 percent deviation from the equilibrium path is corrected in the next period at a rate of −0.65 percent and is statistically significant at the 1 percent significance level. This confirms the presence of a long-run level equilibrium path between real GDP and the selected regressors (total school enrolment, primary; real exchange rate; population; government consumption; investment; inflation; foreign aid; imports; and exports). The regression results for the ARDL model reveal a good fit represented by an estimated R-squared value of 0.85 and an adjusted R-squared value of 0.67, as shown in Table 3.
Part B, regression II of Table 3 presents the long-run coefficient estimates. The results reveal that the key macroeconomic determinants that are significantly associated with long-run GDP growth in Uganda are government consumption, investment, exports and the policy dummy.
The study reveals a positive relationship between government consumption and real GDP growth at the 1 percent significance level in the long run. A 1 percent increase in government consumption results in a 0.20 percent increase in the level of real GDP. These results are supported by Doppelhofer and Weeks [89] who find a positive relationship between government consumption and economic growth in the long run in developing countries.
The study reveals a positive relationship between investment and real GDP growth at the 1 percent significance level in the long run. A 1 percent increase in the level of investment results in a 0.22 percent increase in the level of real GDP. These results are supported by similar studies conducted in developing countries that have found a positive relationship between investment and economic growth in the long run (e.g., [10, 17, 54, 81, 82]).
There is a positive and significant relationship between GDP and exports in the long run at the 1 percent level of significance. A 1 percent increase in exports leads to a 0.12 percent increase in GDP growth (see [14, 16]).
There is also a negative and significant relationship between GDP and the policy dummy for SAPs in Uganda, as a 1 percent increase in implementation of the SAPs leads to a 0.07 percent reduction in real GDP growth.
The study results did not reveal a significant association between population growth, inflation human capital and foreign aid, imports and GDP growth in the long run.
The short-run results for the sensitivity/option analysis are shown in Part A, regression II of Table 3 above. The key macroeconomic determinants that are significantly associated with the growth of real GDP in the short run are initial GDP, inflation, government consumption (percent, GDP), investment, exports, and the policy dummy in both the current and the previous period.
The results show that a 1 percent increase in initial real GDP leads to a 0.28 percent increase in real GDP.
The results reveal a negative association between inflation and economic growth. A 1 percent increase in inflation leads to a 0.90 percent reduction in GDP. These results are supported by a number of empirical growth studies that have also found a negative association between inflation and economic growth in developing countries (e.g., [55, 56, 57, 83, 84, 85, 86]).
The results show that government consumption is positively and significantly associated with the growth of real GDP at the 1 percent significance level. A 1 percent change in government consumption leads to a 0.07 percent increase in the growth of GDP. The positive relationship found between government consumption and economic growth is supported by similar studies in the empirical growth literature that have found a positive relationship between trade openness and economic growth (e.g., [17]).
There is a positive and significant relationship between investment and economic growth at the 1 percent level of significance. A 1 percent increase in investment leads to a 0.15 percent increase in GDP. The results are consistent with the existing empirical growth studies that have found a positive relationship between investment and economic growth (e.g., [10, 17, 88]).
The results show that exports are positively and significantly associated with the growth of real GDP at the 5 percent significance level. A 1 percent change in exports leads to a 0.03 percent increase in GDP growth. The positive relationship found between exports and GDP growth is supported by similar studies in the empirical growth literature (e.g., [14, 90]).
There was a negative and significant relationship between the implementation of the structural adjustment programmes and GDP growth in the current period. A 1 percent increase in the implementation of the SAPs led to a 0.1 reduction in GDP.
The results indicate that in the short run, policy variables contributed to economic growth more than factor accumulation, while in the long run, a mixture of factor accumulation and policy variables was the major driver of economic growth.
3.5 Post-estimation diagnostic tests
The regressions were tested to ascertain their applicability and robustness. Robustness was confirmed by the Breusch-Godfrey serial correlation LM test, Jarque-Bera normality test, recursive stability tests, and Breusch-Pagan-Godfrey heteroscedasticity test. This means that the model has the desired econometric properties of time series data.
Recursive Tests were done using a visual examination of the graphs of the recursive parameter estimates. Additionally, a formal statistical test to test the null hypothesis of model stability was undertaken using the CUSUM test [91]. Figure 2 regression I and regression II illustrate the CUSUM and CUSUMSQ at the 5 percent significance level.
Figure 2.
CUSUM and CUSUMSQ results for the estimated growth equation.
As illustrated in Figure 2, the CUSUM test reveals parameter stability, while the results of the CUSUMQ test reveal variance stability given that the residuals for both tests are within the 5 percent critical lines. According to these tests, our ARDL model is stable and has no serial correlation.
3.5.1 Serial correlation tests of residuals
Serial correlation was undertaken to test whether the residual is correlated with its own lagged values using the Breusch-Godfrey LM test for serial correlation, and the results are presented in Table 4 below.
Breusch-Godfrey serial correlation LM test
Regression I
Regression II
F-statistic
1.332638
Prob. F(3,13)
0.2739
0.0223
Obs*R-squared
7.526409
Prob. Chi-Square(3)
0.1921
0.0004
Table 4.
The Breusch-Godfrey test for serial correlation in the residuals of the regression.
The Breusch-Godfrey serial correlation test statistic for the null hypothesis of no serial correlation (Table 4) for regression I has a probability value of 0.2739, which is greater than 5 percent. Thus, we fail to reject the null hypothesis, which indicates that there is no serial correlation in the residuals.
3.5.2 Heteroscedasticity test
The Breusch-Pagan-Godfrey tests for heteroscedasticity statistic for the null hypothesis of no heteroscedasticity in regressions I and II have probability values of 0.6996 and 0.0612, respectively, which are greater than 5 percent. Thus, we fail to reject the null hypothesis, which indicates that there is no heteroscedasticity in the residuals (Table 5).
Heteroscedasticity test: Breusch-Pagan-Godfrey
Model I (probability)
Model II
F-statistic
0.760385
Prob. F(15,16)
0.6996
0.0612
Obs*R-squared
13.31781
Prob.Chi-Square(15)
0.5778
0.1320
Scaled Explained SS
2.325347
Prob.Chi-Square(15)
0.9999
0.9945
Table 5.
Breusch-Pagan-Godfrey test for heteroscedasticity results.
3.5.3 Normality test
The ARDL model assumes that the residuals are normally distributed. The Jarque-Bera statistic is assumed to have a chi-square (𝜒2) distribution with two degrees of freedom, and the null hypothesis assumes that the errors are normally distributed [92, 93, 94].
As indicated in Figure 3, in regression I, the probability value for the Jarque-Bera statistic is 0.49 with a probability value of 0.782, which is more than 5 percent; hence, the residuals are normally distributed. In regression II, the probability value for the Jarque-Bera statistic is 0.647 with a probability value of 0.724, which is more than 5 percent; hence, the residuals are normally distributed. This means that statistical tests for inference on regression coefficients are reliable, since these tests require that the dependent variable (and hence the residuals) follows a normal distribution.
Figure 3.
Histogram normality test model I.
3.5.4 Ramsey rest test for the functional form
Specification errors can be errors in the specification of the functional form that the equation should take in describing the relationship between the variable. If the F test statistic is greater than the F critical value, we reject the null hypothesis that the true specification is greater than the F critical value, hence reject the null hypothesis that the true specification is linear (which implies that the true specification is non-linear). If we are unable to reject the null, then the results suggest that the true specification is linear and the equation passes the Ramsey Reset test (Table 6).
Ramsey RESET Test
Equation: UNTITLED
Specification: LRGDP LRGDP(−1) LTRO LTRO(−1) LPOPN LINF LINF(−1) LHC LHC(−1) LHC(−2) LGGC LGGC(−1) LGFCF LAID C
Omitted variables: squares of fitted values
Value
df
Probability
t-statistic
0.326505
17
0.7481
F-statistic
0.106606
(1, 17)
0.7480
Table 6.
Ramsey rest test for the functional form test results.
The probability values from the Ramsey rest test for the T and F statistics are greater than 0.05 level of significance, meaning that the estimated model is free from specification errors.
3.6 Conclusion
Attaining high and sustainable economic growth is a major policy objective for any country especially among developing countries. In this paper, we examined the macroeconomic determinants of economic growth in Uganda using the factor accumulation framework for the period 1982–2015.
The autoregressive distributed lag (ARDL) approach to co-integration was used to estimate both the short- and long-run elasticities of the selected macroeconomic determinants. The ARDL bounds testing approach to co-integration in the benchmark regression indicated that the key determinants that are positively associated with growth in GDP in the short run are the initial level of real GDP growth, government consumption and investment, while foreign aid, inflation and a dummy for SAPs were negatively and significantly associated with real GDP growth. The results failed to show that trade openness, population growth and human capital accumulation were significantly associated with real GDP growth in the short run [95, 96, 97, 98].
The study revealed that in the long run, trade openness, population growth and government consumption and investment were positively and significantly associated with GDP growth, while the policy dummy on SAPs was negatively and significantly associated with GDP. In the long run, the study failed to show that inflation, human capital and foreign aid were significantly associated with GDP growth. It can be concluded that in the short run, policy variables contributed to economic growth more than factor accumulation (physical and human capital), while in the long run, a mixture of both factor accumulation and policy variables was the major driver of economic growth.
The study results have significant policy implications for Uganda. They show that investment and population have are significantly associated with economic growth both in the short and long run. Thus, it is recommended that the economic strategies to be adopted should include those that create incentives to attract investment—with an emphasis on the adoption of labour–intensive technologies, on quality–based human capital development. In the short run trade openness, government consumption, foreign aid and inflation are positively and significantly associated with economic growth meaning that the country should pursue policies that enhance trade, government effectiveness, aid effectiveness and economic management.
The study found that the key determinants that were positively associated with growth in GDP in the short run were the initial level of GDP growth, government consumption, investment and a dummy for SAPs, while foreign aid and inflation were negatively associated with GDP growth. The results failed to show that trade openness, population growth and human capital accumulation were significantly associated with GDP growth in the short run. In the long run, the study revealed that trade openness, population growth, government consumption and investment were positively associated with GDP, while the policy dummy on SAPs was negatively associated with GDP growth. In the long run, the study failed to show that inflation, human capital and foreign aid were significantly associated with growth in GDP.
These results have significant policy implications for Uganda, both in the short and long run. In the short run it is recommended that economic strategies that would spur accumulation of physical capital/Investment, increase government consumption, improve price stability be pursued while in the long run, strategies that improve trade openness, population growth, government consumption and investment should be pursued.
Acknowledgments
We would like to acknowledge Prof John Dumba Ssentamu and Associate Professor Eria Hisali, for their insurmountable technical contribution to this paper through their reviews and comments.
\n',keywords:"Uganda, Economic growth, Auto Regressive Distribute Lag Model",chapterPDFUrl:"https://cdn.intechopen.com/pdfs/79329.pdf",chapterXML:"https://mts.intechopen.com/source/xml/79329.xml",downloadPdfUrl:"/chapter/pdf-download/79329",previewPdfUrl:"/chapter/pdf-preview/79329",totalDownloads:151,totalViews:0,totalCrossrefCites:0,dateSubmitted:"September 3rd 2021",dateReviewed:"September 17th 2021",datePrePublished:"November 14th 2021",datePublished:null,dateFinished:"November 14th 2021",readingETA:"0",abstract:"This paper investigated the determinants of economic growth in Uganda for the period 1982–2015 using the autoregressive distributed lag (ARDL) mode. The paper was motivated by the impressive economic performance of Uganda since 1986 that made her graduate from a “failed state” to a “mature reformer” in a short time. The paper established that while the initial level of GDP growth, government consumption and investment positively affected Uganda’s economic growth in the short run, inflation, foreign aid and a policy dummy variable representing structural adjustment programmes negatively impacted GDP growth. The results revealed that in the long run, trade openness, population growth, government consumption and investment positively influenced GDP growth in Uganda. The results failed to show a significant relationship between trade openness, population growth and human capital accumulation and economic growth in the short run. The study also failed to show a significant relationship between inflation, human capital and foreign aid and economic growth in the long run. The paper recommends policies that enhances sound macroeconomic fundamentals such as price stability, investment promotion, trade openness, increased government consumption, increased population growth and effective foreign aid.",reviewType:"peer-reviewed",bibtexUrl:"/chapter/bibtex/79329",risUrl:"/chapter/ris/79329",signatures:"Richard Sendi, John Bbale Mayanja and Enock Nyorekwa",book:{id:"10977",type:"book",title:"Macroeconomic Analysis for Economic Growth",subtitle:null,fullTitle:"Macroeconomic Analysis for Economic Growth",slug:null,publishedDate:null,bookSignature:"Dr. Musa Jega Ibrahim",coverURL:"https://cdn.intechopen.com/books/images_new/10977.jpg",licenceType:"CC BY 3.0",editedByType:null,isbn:"978-1-83969-882-8",printIsbn:"978-1-83969-881-1",pdfIsbn:"978-1-83969-883-5",isAvailableForWebshopOrdering:!0,editors:[{id:"107299",title:"Dr.",name:"Musa Jega",middleName:null,surname:"Ibrahim",slug:"musa-jega-ibrahim",fullName:"Musa Jega Ibrahim"}],productType:{id:"1",title:"Edited Volume",chapterContentType:"chapter",authoredCaption:"Edited by"}},authors:null,sections:[{id:"sec_1",title:"1. Introduction",level:"1"},{id:"sec_2",title:"2. A review of empirical literature",level:"1"},{id:"sec_3",title:"3. Analytical framework and data",level:"1"},{id:"sec_3_2",title:"3.1 Theoretical framework",level:"2"},{id:"sec_4_2",title:"3.2 Estimation techniques",level:"2"},{id:"sec_4_3",title:"3.2.1 Estimation of the error correction-based ARDL model",level:"3"},{id:"sec_6_2",title:"3.3 Data type and sources",level:"2"},{id:"sec_7_2",title:"3.4 Analysis and discussion of results",level:"2"},{id:"sec_7_3",title:"Table 1.",level:"3"},{id:"sec_8_3",title:"Table 2.",level:"3"},{id:"sec_9_3",title:"3.4.3 Relative superiority of the selected models",level:"3"},{id:"sec_10_3",title:"Table 3.",level:"3"},{id:"sec_12_2",title:"3.5 Post-estimation diagnostic tests",level:"2"},{id:"sec_12_3",title:"Table 4.",level:"3"},{id:"sec_13_3",title:"Table 5.",level:"3"},{id:"sec_14_3",title:"3.5.3 Normality test",level:"3"},{id:"sec_15_3",title:"Table 6.",level:"3"},{id:"sec_17_2",title:"3.6 Conclusion",level:"2"},{id:"sec_19",title:"Acknowledgments",level:"1"}],chapterReferences:[{id:"B1",body:'Lucas Jr, R. E. 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Biometrika, 75(2), 335-346.'},{id:"B77",body:'Narayan, P. K., & Smyth, R. (2008). Energy consumption and real GDP in G7 countries: new evidence from panel cointegration with structural breaks. Energy Economics, 30(5), 2331-2341.'},{id:"B78",body:'Verma, R. (2007). Savings, investment and growth in India: An application of the ARDL bounds testing approach. South Asia Economic Journal, 8(1), 87-98.'},{id:"B79",body:'Tolo, W. B. J. (2011). The determinants of economic growth in the Philippines: A new look. IMF Working Papers, 1-24.'},{id:"B80",body:'Abu‐Bader, S., & Abu‐Qarn, A. S. (2008). Financial development and economic growth: empirical evidence from six MENA countries. Review of Development Economics, 12(4), 803-817.'},{id:"B81",body:'Asheghian, Parviz. “Determinants of economic growth in Japan: The role of foreign direct investment.” Global Economy Journal 9.3 (2009): 1850171.'},{id:"B82",body:'Bleaney, M., Gemmell, N., & Kneller, R. (2001). Testing the endogenous growth model: public expenditure, taxation, and growth over the long run. Canadian Journal of Economics/Revue canadienne d\'économique, 34(1), 36-57.'},{id:"B83",body:'Barro, R. J. (1999). Determinants of economic growth: implications of the global evidence for Chile. Cuadernos de economía, 443-478.'},{id:"B84",body:'Bayraktar, B. (2006). Investigation on sources of growth for Turkey. Canadian Journal of Development Studies/Revue canadienne d’études du développement, 27(1), 25-38.'},{id:"B85",body:'Rao, B. B., & Hassan, G. (2011). Determinants of the long-run growth rate of Bangladesh. Applied Economics Letters, 18(7), 655-658.'},{id:"B86",body:'Burnside, C., & Dollar, D. (2000). Aid, policies, and growth. American economic review, 90(4), 847-868.'},{id:"B87",body:'Parjiono, Beg, A. R. A., & Monypenny, R. (2013). The driving forces of the level and the growth rate of real per capita income in Indonesia. Applied Economics, 45(17), 2389-2400.'},{id:"B88",body:'Freire-Seren, M. J. (2002). On the relationship between human capital accumulation and economic growth. Applied Economics Letters, 9(12), 805-808.'},{id:"B89",body:'Doppelhofer, G., & Weeks, M. (2011). Robust growth determinants.'},{id:"B90",body:'Ahmad, J., & Harnhirun, S. (1996). Cointegration and causality between exports and economic growth: evidence from the ASEAN countries. The Canadian Journal of Economics/Revue canadienne d\'Economique, 29, S413-S416.'},{id:"B91",body:'Studenmund, A. H., & Econometrics, H. U. (2001). Using econometrics: A Practical Guide. Addison-Wesley Educational Publishers.'},{id:"B92",body:'Jarque, C. M., & Bera, A. K. (1980). Efficient tests for normality, homoscedasticity and serial independence of regression residuals. Economics letters, 6(3), 255-259.'},{id:"B93",body:'Jarque, C. M., & Bera, A. K. (1987). A test for normality of observations and regression residuals. International Statistical Review/Revue Internationale de Statistique, 163-172.'},{id:"B94",body:'Bera, A. K., & Jarque, C. M. (1981). Efficient tests for normality, homoscedasticity and serial independence of regression residuals: Monte Carlo evidence. Economics letters, 7(4), 313-318.'},{id:"B95",body:'Capolupo, R. (2009). The new growth theories and their empirics after twenty years. Economics, 3(1).'},{id:"B96",body:'Havi, E. D. K., Enu, P., Osei-Gyimah, F., Attah-Obeng, P., & Opoku, C. D. K. (2013). Macroeconomic determinants of economic growth in Ghana: Cointegration approach. European Scientific Journal, 9(19).'},{id:"B97",body:'Steven, R., Jeffrey, S., & Jong-Wha, L. (2001). The determinants and prospects of economic growth in Asia. International Economic Journal, 15(3), 1-29.'},{id:"B98",body:'Veiderpass, A., & Andersson, P. (2007). Foreign aid, economic growth and efficiency development. Swedish Agency for Development Evaluation.'}],footnotes:[],contributors:[{corresp:"yes",contributorFullName:"Richard Sendi",address:"sendirichard@yahoo.com",affiliation:'
The Open Access model is applied to all of our publications and is designed to eliminate subscriptions and pay-per-view fees. This approach ensures free, immediate access to full text versions of your research.
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Choosing to publish with IntechOpen ensures the following benefits:
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Benefits of Publishing with IntechOpen
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Proven world leader in Open Access book publishing with over 10 years experience
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As a gold Open Access publisher, an Open Access Publishing Fee is payable on acceptance following peer review of the manuscript. In return, we provide high quality publishing services and exclusive benefits for all contributors. IntechOpen is the trusted publishing partner of over 140,000 international scientists and researchers.
\n\n
The Open Access Publishing Fee (OAPF) is payable only after your book chapter, monograph or journal article is accepted for publication.
\n\n
OAPF Publishing Options
\n\n
\n\t
1,400 GBP Chapter - Edited Volume
\n\t
850 GBP Chapter - Book Series Topic (Annual Volume)
\n\t
10,000 GBP Monograph - Long Form
\n\t
4,000 GBP Compacts Monograph - Short Form
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850 GBP Journal Article (Across Portfolio)
\n
\n\n
During the launching phase journals do not charge an APC, rather they will be funded by IntechOpen.
\n\n
*These prices do not include Value-Added Tax (VAT). Residents of European Union countries need to add VAT based on the specific rate in their country of residence. Institutions and companies registered as VAT taxable entities in their own EU member state will not pay VAT as long as provision of the VAT registration number is made during the application process. This is made possible by the EU reverse charge method.
\n\n
Services included are:
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\n\t
An online manuscript tracking system to facilitate your work
\n\t
Personal contact and support throughout the publishing process from your dedicated Author Service Manager
\n\t
Assurance that your manuscript meets the highest publishing standards
\n\t
English language copyediting and proofreading, including the correction of grammatical, spelling, and other common errors
\n\t
XML Typesetting and pagination - web (PDF, HTML) and print files preparation
\n\t
Discoverability - electronic citation and linking via DOI
\n\t
Permanent and unrestricted online access to your work
\n
\n\n
What isn't covered by the Open Access Publishing Fee?
\n\n
If your manuscript:
\n\n
\n\t
Exceeds the number of pages defined by the publishing guidelines, an additional fee per page may be required
\n\t
If a manuscript requires Heavy Editing or Language Polishing, this will incur additional fees.
\n
\n\n
Your Author Service Manager will inform you of any items not covered by the OAPF and provide exact information regarding those additional costs before proceeding.
\n\n
Open Access Funding
\n\n
To explore funding opportunities and learn more about how you can finance your IntechOpen publication, go to our Open Access Funding page. IntechOpen offers expert assistance to all of its Authors. We can support you in approaching funding bodies and institutions in relation to publishing fees by providing information about compliance with the Open Access policies of your funder or institution. We can also assist with communicating the benefits of Open Access in order to support and strengthen your funding request and provide personal guidance through your application process. You can contact us at funders@intechopen.com for further details or assistance.
\n\n
For Authors who are still unable to obtain funding from their institutions or research funding bodies for individual projects, IntechOpen does offer the possibility of applying for a Waiver to offset some or all processing feed. Details regarding our Waiver Policy can be found here.
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Added Value of Publishing with IntechOpen
\n\n
Choosing to publish with IntechOpen ensures the following benefits:
\n\n
\n\t
Indexing and listing across major repositories, see details ...
\n\t
Long-term archiving
\n\t
Visibility on the world's strongest OA platform
\n\t
Live Performance Metrics to track readership and the impact of your chapter
\n\t
Dissemination and Promotion
\n
\n\n
Benefits of Publishing with IntechOpen
\n\n
\n\t
Proven world leader in Open Access book publishing with over 10 years experience
\n\t
+5,700 OA books published
\n\t
Most competitive prices in the market
\n\t
Fully compliant with OA funding requirements
\n\t
Optimized processes that assure your research is made available to the scientific community without delay
\n\t
Personal support during every step of the publication process
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+184,650 citations in Web of Science databases
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Currently strongest OA platform with over 175 million downloads
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In most of the cases, the structures of drugs or drug candidates and the interacting residues on the target proteins are also presented. In addition, a few successful examples of drug repurposing using molecular docking are mentioned in this chapter. It should provide us with confidence that the docking will be extensively employed in the industry and basic research. Moreover, we should actively apply molecular docking and related technology to create new therapies for diseases.",book:{id:"6365",slug:"molecular-docking",title:"Molecular Docking",fullTitle:"Molecular Docking"},signatures:"Mark Andrew Phillips, Marisa A. Stewart, Darby L. Woodling and\nZhong-Ru Xie",authors:[{id:"214567",title:"Prof.",name:"Zhong-Ru",middleName:null,surname:"Xie",slug:"zhong-ru-xie",fullName:"Zhong-Ru Xie"},{id:"223007",title:"Ms.",name:"Marisa A.",middleName:null,surname:"Stewart",slug:"marisa-a.-stewart",fullName:"Marisa A. 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Mainly, the versatile techniques of ultra−/high-performance liquid chromatography (UPLC/HPLC) are in use for the analysis of assay and organic impurities/related substances/degradation products of a drug substance or drug product or intermediate or raw material of pharmaceuticals. A suitable analytical method is developed only after evaluating the major and critical separation parameters of chromatography (examples for UPLC/HPLC are selection of diluent, wavelength, detector, stationary phase, column temperature, flow rate, solvent system, elution mode, and injection volume, etc.). The analytical method development is a process of proving the developed analytical method is suitable for its intended use for the quantitative estimation of the targeted analyte present in pharmaceutical drugs. And it mostly plays a vital role in the development and manufacture of pharmaceuticals drugs.",book:{id:"8912",slug:"biochemical-analysis-tools-methods-for-bio-molecules-studies",title:"Biochemical Analysis Tools",fullTitle:"Biochemical Analysis Tools - Methods for Bio-Molecules Studies"},signatures:"Narasimha S. Lakka and Chandrasekar Kuppan",authors:[{id:"304950",title:"Prof.",name:"Chandrasekar",middleName:null,surname:"Kuppan",slug:"chandrasekar-kuppan",fullName:"Chandrasekar Kuppan"},{id:"309984",title:"Mr.",name:"Narasimha S",middleName:null,surname:"Lakka",slug:"narasimha-s-lakka",fullName:"Narasimha S Lakka"}]},{id:"72074",title:"The Chemistry Behind Plant DNA Isolation Protocols",slug:"the-chemistry-behind-plant-dna-isolation-protocols",totalDownloads:3797,totalCrossrefCites:4,totalDimensionsCites:7,abstract:"Various plant species are biochemically heterogeneous in nature, a single deoxyribose nucleic acid (DNA) isolation protocol may not be suitable. There have been continuous modification and standardization in DNA isolation protocols. Most of the plant DNA isolation protocols used today are modified versions of hexadecyltrimethyl-ammonium bromide (CTAB) extraction procedure. Modification is usually performed in the concentration of chemicals used during the extraction procedure according to the plant species and plant part used. Thus, understanding the role of each chemical (viz. CTAB, NaCl, PVP, ethanol, and isopropanol) used during the DNA extraction procedure will benefit to set or modify protocols for more precisions. A review of the chemicals used in the CTAB method of DNA extraction and their probable functions on the highly evolved yet complex to students and researchers has been summarized.",book:{id:"8912",slug:"biochemical-analysis-tools-methods-for-bio-molecules-studies",title:"Biochemical Analysis Tools",fullTitle:"Biochemical Analysis Tools - Methods for Bio-Molecules Studies"},signatures:"Jina Heikrujam, Rajkumar Kishor and Pranab Behari Mazumder",authors:[{id:"74521",title:"Dr.",name:"Rajkumar",middleName:null,surname:"Kishor",slug:"rajkumar-kishor",fullName:"Rajkumar Kishor"},{id:"309357",title:"Prof.",name:"Pranab Behari",middleName:null,surname:"Mazumder",slug:"pranab-behari-mazumder",fullName:"Pranab Behari Mazumder"},{id:"318351",title:"Ph.D. Student",name:"Jina",middleName:null,surname:"Heikrujam",slug:"jina-heikrujam",fullName:"Jina Heikrujam"}]},{id:"64549",title:"Plant Lipid Metabolism",slug:"plant-lipid-metabolism",totalDownloads:2677,totalCrossrefCites:8,totalDimensionsCites:14,abstract:"In plants, the synthesis of fatty acids takes place in the chloroplast and the fatty acid synthase is prokaryotic type. In plants, the structure of membrane lipids is different from that of eukaryotic cells. The membranes of the chloroplasts are essentially formed of galatolipids. This chapter will also focus on the structure and biosynthesis of fatty acids and membrane lipids in plants. Lipids of seeds are essentially composed of TAG; it would be interesting to describe their synthesis during the maturation of the seeds. Some plants contain in their reserve lipids unconventional fatty acids such as gamma linolenic acid in Borrago officinalis L., short-chain fatty acids C: 12 and C: 10, fatty acids with very long chains, and fatty acids that are cyclical. All of these fatty acids can have industrial and/or pharmaceutical applications.",book:{id:"7036",slug:"advances-in-lipid-metabolism",title:"Advances in Lipid Metabolism",fullTitle:"Advances in Lipid Metabolism"},signatures:"Fatiha AID",authors:[{id:"256576",title:"Prof.",name:"Fatiha",middleName:null,surname:"Aid",slug:"fatiha-aid",fullName:"Fatiha Aid"}]},{id:"66369",title:"General Perception of Liposomes: Formation, Manufacturing and Applications",slug:"general-perception-of-liposomes-formation-manufacturing-and-applications",totalDownloads:3320,totalCrossrefCites:17,totalDimensionsCites:40,abstract:"Liposomes are currently part of the most reputed carriers for various molecular species, from small and simple to large and complex molecules. Since their discovery, liposomes have been subject to extensive evolution, in terms of composition, manufacturing and applications, which led to several openings in both basic and applied life sciences. However, most of the advances in liposome research have been more devoted to launching new developments than improving the existing technology for potential implementation. For instance, the evolution of the conventional lipid hydration methods to novel microfluidic technologies has permitted upscale production, but with increase in manufacturing cost and persistent use of organic solvents. This chapter intends to present general concepts in liposome technology, highlighting some longstanding bottlenecks that remain challenging to the preparation, characterization and applications of liposomal systems. This would enhance the understanding of the gaps in the field and, hence, provide directions for future research and developments.",book:{id:"8095",slug:"liposomes-advances-and-perspectives",title:"Liposomes",fullTitle:"Liposomes - Advances and Perspectives"},signatures:"Christian Isalomboto Nkanga, Alain Murhimalika Bapolisi, Nnamdi Ikemefuna Okafor and Rui Werner Maçedo Krause",authors:[{id:"284670",title:"Prof.",name:"Rui",middleName:null,surname:"Krause",slug:"rui-krause",fullName:"Rui Krause"},{id:"284672",title:"Mr.",name:"Alain",middleName:null,surname:"Bapolisi",slug:"alain-bapolisi",fullName:"Alain Bapolisi"},{id:"284673",title:"MSc.",name:"Christian",middleName:null,surname:"Nkanga",slug:"christian-nkanga",fullName:"Christian Nkanga"},{id:"284675",title:"Mr.",name:"Okafor",middleName:null,surname:"Nnamdi",slug:"okafor-nnamdi",fullName:"Okafor Nnamdi"}]},{id:"61865",title:"A Click Chemistry Approach to Tetrazoles: Recent Advances",slug:"a-click-chemistry-approach-to-tetrazoles-recent-advances",totalDownloads:2687,totalCrossrefCites:2,totalDimensionsCites:4,abstract:"Introduction to tetrazole and click chemistry approaches was briefed in a concise way in order to help the readers have a basic understanding. Tetrazole and its derivatives play very important role in medicinal and pharmaceutical applications. The synthesis of tetrazole derivatives can be approached in ecofriendly approaches such as the use of water as solvent, moderate conditions, nontoxic, easy extractions, easy setup, low cost, etc. with good to excellent yields.",book:{id:"6365",slug:"molecular-docking",title:"Molecular Docking",fullTitle:"Molecular Docking"},signatures:"Ravi Varala and Bollikolla Hari Babu",authors:[{id:"212519",title:"Dr.",name:"Varala",middleName:null,surname:"Ravi",slug:"varala-ravi",fullName:"Varala Ravi"},{id:"221476",title:"Dr.",name:"Bollikolla",middleName:null,surname:"Hari Babu",slug:"bollikolla-hari-babu",fullName:"Bollikolla Hari Babu"}]}],onlineFirstChaptersFilter:{topicId:"43",limit:6,offset:0},onlineFirstChaptersCollection:[{id:"82531",title:"Abnormal Iron Metabolism and Its Effect on Dentistry",slug:"abnormal-iron-metabolism-and-its-effect-on-dentistry",totalDownloads:12,totalDimensionsCites:0,doi:"10.5772/intechopen.104502",abstract:"Iron is a necessary micro-nutrient for proper functioning of the erythropoietic, oxidative and cellular metabolism. The iron balance in the body adversely affects the normal physiologic functioning of the body and structures in the oral cavity. Various abnormalities develop owing to improper iron metabolism in the body which reflects in the oral cavity. The toxicity of iron has to be well understood to immediately identify the hazardous effects which arise owing to it and to manage it. It has been very well mentioned in the chapter. The manifestations of defects of iron metabolism in the oral cavity should be carefully studied to improve the prognosis of the treatment of the same. Disorders related to iron metabolism should be managed for improvement in the quality of life of the patient.",book:{id:"10842",title:"Iron Metabolism - A Double-Edged Sword",coverURL:"https://cdn.intechopen.com/books/images_new/10842.jpg"},signatures:"Chinmayee Dahihandekar and Sweta Kale Pisulkar"},{id:"82403",title:"Use of Plant Secondary Metabolites to Reduce Crop Biotic and Abiotic Stresses: A Review",slug:"use-of-plant-secondary-metabolites-to-reduce-crop-biotic-and-abiotic-stresses-a-review",totalDownloads:19,totalDimensionsCites:0,doi:"10.5772/intechopen.104553",abstract:"Plant secondary metabolites (PSM) are small molecules of organic compounds produced in plant metabolism that have various ecological functions, such as defense against pathogens, herbivores, and neighboring plants. They can also help to reduce abiotic stresses, such as drought, salinity, temperature, and UV. This chapter reviewed the ecological functions of the PSM and how people utilize these metabolites to reduce crop biotic and abiotic stresses in agriculture. Specific topics covered in this review are (1) extraction of PSM from plant parts and its application on crops; (2) screening of crop/cover crop germplasms for high PSM content and with resistance to pathogens, herbivores, and/or neighboring plants; (3) regulation of PSM biosynthesis (including plant hormones and defense activators) to increase plant readiness for defense; (4) transcriptome and genome technology improvements in the last decade leading to valuable tools to characterize differential gene expression and gene composition in a genome, and lineage-specific gene family expansion and contraction. In addition, there is a critical need to understand how the biosynthesis and release of allelochemicals occur. Filling this knowledge gap will help us to improve and encourage sustainable weed control practices in agriculture.",book:{id:"11331",title:"Secondary Metabolites - Trends and Reviews",coverURL:"https://cdn.intechopen.com/books/images_new/11331.jpg"},signatures:"Ziming Yue, Varsha Singh, Josiane Argenta, Worlanyo Segbefia, Alyssa Miller and Te Ming Tseng"},{id:"81728",title:"Plant Secondary Metabolites: Therapeutic Potential and Pharmacological Properties",slug:"plant-secondary-metabolites-therapeutic-potential-and-pharmacological-properties",totalDownloads:30,totalDimensionsCites:0,doi:"10.5772/intechopen.103698",abstract:"Plants are an essential source for discovering novel medical compounds for drug development, and secondary metabolites are sources of medicines from plants. Secondary metabolites include alkaloids, flavonoids, terpenoids, tannins, coumarins, quinones, carotenoids, and steroids. Each year, several new secondary metabolites are extracted from plants, providing a source of possibilities to investigate against malignant illnesses, despite certain natural chemicals having distinct anticancer activities according to their physicochemical features. Secondary metabolites found in plants are frequently great leads for therapeutic development. However, changes in the molecular structure of these compounds are improving their anticancer activity and selectivity and their absorption, distribution, metabolism, and excretion capacities while minimizing their toxicity and side effects. In this section, we will discuss the most significant breakthroughs in the field of plant secondary metabolites, some of which are currently in clinical use and others that are in clinical trials as anticancer drugs. This study gives an up-to-date and thorough summary of secondary plant metabolites and their antioxidant, antibacterial, and anticancer effects. Furthermore, antioxidant and antibacterial, and anticancer effects of secondary metabolites are addressed. As a result, this article will serve as a thorough, quick reference for people interested in secondary metabolite antioxidants, anticancer, and antibacterial properties.",book:{id:"11331",title:"Secondary Metabolites - Trends and Reviews",coverURL:"https://cdn.intechopen.com/books/images_new/11331.jpg"},signatures:"Muhammad Zeeshan Bhatti, Hammad Ismail and Waqas Khan Kayani"},{id:"80495",title:"Iron in Cell Metabolism and Disease",slug:"iron-in-cell-metabolism-and-disease",totalDownloads:22,totalDimensionsCites:0,doi:"10.5772/intechopen.101908",abstract:"Iron is the trace element. We get the iron from the dietary sources. The enterocytes lining the upper duodenal of the intestine absorb the dietary iron through a divalent metal transporter (DMT1). The absorbed ferrous iron is oxidized to ferric iron in the body. This ferric iron from the blood is carried to different tissues by an iron transporting protein, transferrin. The cells in the tissues take up this ferric form of iron by internalizing the apo transferrin with its receptors on them. The apo transferrin complex in the cells get dissociated resulting in the free iron in cell which is utilized for cellular purposes or stored in the bound form to an iron storage protein, ferritin. The physiological levels of iron are critical for the normal physiology and pathological outcomes, hence the iron I rightly called as double-edged sword. This chapter on iron introduces the readers basic information of iron, cellular uptake, metabolism, and its role cellular physiology and provides the readers with the scope and importance of research on iron that hold the great benefit for health care and personalized medicine or diseases specific treatment strategies, blood transfusions and considerations.",book:{id:"10842",title:"Iron Metabolism - A Double-Edged Sword",coverURL:"https://cdn.intechopen.com/books/images_new/10842.jpg"},signatures:"Eeka Prabhakar"},{id:"81233",title:"Secondary Metabolites of Fruits and Vegetables with Antioxidant Potential",slug:"secondary-metabolites-of-fruits-and-vegetables-with-antioxidant-potential",totalDownloads:43,totalDimensionsCites:1,doi:"10.5772/intechopen.103707",abstract:"An antioxidant is of great interest among researchers, scientists, nutritionists, and the public because of its ability to prevent oxidative damage, as indicated by various studies. This chapter mainly focuses on the free radicals and their types; antioxidants and their mode of action against free radicals; fruits, vegetables, and their byproducts as a source of antioxidants; and various analytical methods employed for assessing antioxidant activity. Antioxidants discussed in this chapter are ascorbic acid, Vitamin E, carotenoids and polyphenols, and their mechanism of action. Different antioxidant activity assay techniques have been reported. Fruits and vegetables are abundant sources of these secondary metabolites. The waste generated during processing has many bioactive materials, which possibly be used in value-added by-products.",book:{id:"11331",title:"Secondary Metabolites - Trends and Reviews",coverURL:"https://cdn.intechopen.com/books/images_new/11331.jpg"},signatures:"Ravneet Kaur, Shubhra Shekhar and Kamlesh Prasad"},{id:"81044",title:"Metabolomics and Genetic Engineering for Secondary Metabolites Discovery",slug:"metabolomics-and-genetic-engineering-for-secondary-metabolites-discovery",totalDownloads:7,totalDimensionsCites:0,doi:"10.5772/intechopen.102838",abstract:"Since 1940s, microbial secondary metabolites (SMs) have attracted the attention of the scientific community. As a result, intensive researches have been conducted in order to discover and identify novel microbial secondary metabolites. Since, the discovery of novel secondary metabolites has been decreasing significantly due to many factors such as 1) unculturable microbes 2) traditional detection techniques 3) not all SMs expressed in the lab. As a result, searching for new techniques which can overcome the previous challenges was one of the most priority objectives. Therefore, the development of omics-based techniques such as genomics and metabolomic have revealed the potential of discovering novel SMs which were coded in the microorganisms’ DNA but not expressed in the lab or might be produced in undetectable amount by detecting the biosynthesis gene clusters (BGCs) that are associated with the biosynthesis of secondary metabolites. Nowadays, the integration of metabolomics and gene editing techniques such as CRISPR-Cas9 provide a successful platform for the detection and identification of known and unknown secondary metabolites also to increase secondary metabolites production.",book:{id:"11331",title:"Secondary Metabolites - Trends and Reviews",coverURL:"https://cdn.intechopen.com/books/images_new/11331.jpg"},signatures:"Ahmed M. Shuikan, Wael N. Hozzein, Rakan M. Alshuwaykan and Ibrahim A. 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The whole process of submitting an article and editing of the submitted article goes extremely smooth and fast, the number of reads and downloads of chapters is high, and the contributions are also frequently cited.",author:{id:"55578",name:"Antonio",surname:"Jurado-Navas",institutionString:null,profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bRisIQAS/Profile_Picture_1626166543950",slug:"antonio-jurado-navas",institution:{id:"720",name:"University of Malaga",country:{id:null,name:"Spain"}}}},{id:"6",text:"It is great to work with the IntechOpen to produce a worthwhile collection of research that also becomes a great educational resource and guide for future research endeavors.",author:{id:"259298",name:"Edward",surname:"Narayan",institutionString:null,profilePictureURL:"https://mts.intechopen.com/storage/users/259298/images/system/259298.jpeg",slug:"edward-narayan",institution:{id:"3",name:"University of Queensland",country:{id:null,name:"Australia"}}}}]},series:{item:{id:"11",title:"Biochemistry",doi:"10.5772/intechopen.72877",issn:"2632-0983",scope:"Biochemistry, the study of chemical transformations occurring within living organisms, impacts all areas of life sciences, from molecular crystallography and genetics to ecology, medicine, and population biology. Biochemistry examines macromolecules - proteins, nucleic acids, carbohydrates, and lipids – and their building blocks, structures, functions, and interactions. Much of biochemistry is devoted to enzymes, proteins that catalyze chemical reactions, enzyme structures, mechanisms of action and their roles within cells. Biochemistry also studies small signaling molecules, coenzymes, inhibitors, vitamins, and hormones, which play roles in life processes. Biochemical experimentation, besides coopting classical chemistry methods, e.g., chromatography, adopted new techniques, e.g., X-ray diffraction, electron microscopy, NMR, radioisotopes, and developed sophisticated microbial genetic tools, e.g., auxotroph mutants and their revertants, fermentation, etc. More recently, biochemistry embraced the ‘big data’ omics systems. Initial biochemical studies have been exclusively analytic: dissecting, purifying, and examining individual components of a biological system; in the apt words of Efraim Racker (1913 –1991), “Don’t waste clean thinking on dirty enzymes.” Today, however, biochemistry is becoming more agglomerative and comprehensive, setting out to integrate and describe entirely particular biological systems. The ‘big data’ metabolomics can define the complement of small molecules, e.g., in a soil or biofilm sample; proteomics can distinguish all the comprising proteins, e.g., serum; metagenomics can identify all the genes in a complex environment, e.g., the bovine rumen. This Biochemistry Series will address the current research on biomolecules and the emerging trends with great promise.",coverUrl:"https://cdn.intechopen.com/series/covers/11.jpg",latestPublicationDate:"August 2nd, 2022",hasOnlineFirst:!0,numberOfPublishedBooks:33,editor:{id:"31610",title:"Dr.",name:"Miroslav",middleName:null,surname:"Blumenberg",slug:"miroslav-blumenberg",fullName:"Miroslav Blumenberg",profilePictureURL:"https://mts.intechopen.com/storage/users/31610/images/system/31610.jpg",biography:"Miroslav Blumenberg, Ph.D., was born in Subotica and received his BSc in Belgrade, Yugoslavia. He completed his Ph.D. at MIT in Organic Chemistry; he followed up his Ph.D. with two postdoctoral study periods at Stanford University. Since 1983, he has been a faculty member of the RO Perelman Department of Dermatology, NYU School of Medicine, where he is codirector of a training grant in cutaneous biology. Dr. Blumenberg’s research is focused on the epidermis, expression of keratin genes, transcription profiling, keratinocyte differentiation, inflammatory diseases and cancers, and most recently the effects of the microbiome on the skin. He has published more than 100 peer-reviewed research articles and graduated numerous Ph.D. and postdoctoral students.",institutionString:null,institution:{name:"New York University Langone Medical Center",institutionURL:null,country:{name:"United States of America"}}},editorTwo:null,editorThree:null},subseries:{paginationCount:4,paginationItems:[{id:"14",title:"Cell and Molecular Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/14.jpg",isOpenForSubmission:!0,editor:{id:"165627",title:"Dr.",name:"Rosa María",middleName:null,surname:"Martínez-Espinosa",slug:"rosa-maria-martinez-espinosa",fullName:"Rosa María Martínez-Espinosa",profilePictureURL:"https://mts.intechopen.com/storage/users/165627/images/system/165627.jpeg",biography:"Dr. Rosa María Martínez-Espinosa has been a Spanish Full Professor since 2020 (Biochemistry and Molecular Biology) and is currently Vice-President of International Relations and Cooperation development and leader of the research group 'Applied Biochemistry” (University of Alicante, Spain). Other positions she has held at the university include Vice-Dean of Master Programs, Vice-Dean of the Degree in Biology and Vice-Dean for Mobility and Enterprise and Engagement at the Faculty of Science (University of Alicante). She received her Bachelor in Biology in 1998 (University of Alicante) and her PhD in 2003 (Biochemistry, University of Alicante). She undertook post-doctoral research at the University of East Anglia (Norwich, U.K. 2004-2005; 2007-2008).\nHer multidisciplinary research focuses on investigating archaea and their potential applications in biotechnology. She has an H-index of 21. She has authored one patent and has published more than 70 indexed papers and around 60 book chapters.\nShe has contributed to more than 150 national and international meetings during the last 15 years. Her research interests include archaea metabolism, enzymes purification and characterization, gene regulation, carotenoids and bioplastics production, antioxidant\ncompounds, waste water treatments, and brines bioremediation.\nRosa María’s other roles include editorial board member for several journals related\nto biochemistry, reviewer for more than 60 journals (biochemistry, molecular biology, biotechnology, chemistry and microbiology) and president of several organizing committees in international meetings related to the N-cycle or respiratory processes.",institutionString:null,institution:{name:"University of Alicante",institutionURL:null,country:{name:"Spain"}}},editorTwo:null,editorThree:null},{id:"15",title:"Chemical Biology",coverUrl:"https://cdn.intechopen.com/series_topics/covers/15.jpg",isOpenForSubmission:!0,editor:{id:"441442",title:"Dr.",name:"Şükrü",middleName:null,surname:"Beydemir",slug:"sukru-beydemir",fullName:"Şükrü Beydemir",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0033Y00003GsUoIQAV/Profile_Picture_1634557147521",biography:"Dr. Şükrü Beydemir obtained a BSc in Chemistry in 1995 from Yüzüncü Yıl University, MSc in Biochemistry in 1998, and PhD in Biochemistry in 2002 from Atatürk University, Turkey. He performed post-doctoral studies at Max-Planck Institute, Germany, and University of Florence, Italy in addition to making several scientific visits abroad. He currently works as a Full Professor of Biochemistry in the Faculty of Pharmacy, Anadolu University, Turkey. Dr. Beydemir has published over a hundred scientific papers spanning protein biochemistry, enzymology and medicinal chemistry, reviews, book chapters and presented several conferences to scientists worldwide. He has received numerous publication awards from various international scientific councils. He serves in the Editorial Board of several international journals. Dr. Beydemir is also Rector of Bilecik Şeyh Edebali University, Turkey.",institutionString:null,institution:{name:"Anadolu University",institutionURL:null,country:{name:"Turkey"}}},editorTwo:{id:"13652",title:"Prof.",name:"Deniz",middleName:null,surname:"Ekinci",slug:"deniz-ekinci",fullName:"Deniz Ekinci",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002aYLT1QAO/Profile_Picture_1634557223079",biography:"Dr. Deniz Ekinci obtained a BSc in Chemistry in 2004, MSc in Biochemistry in 2006, and PhD in Biochemistry in 2009 from Atatürk University, Turkey. He studied at Stetson University, USA, in 2007-2008 and at the Max Planck Institute of Molecular Cell Biology and Genetics, Germany, in 2009-2010. Dr. Ekinci currently works as a Full Professor of Biochemistry in the Faculty of Agriculture and is the Head of the Enzyme and Microbial Biotechnology Division, Ondokuz Mayıs University, Turkey. He is a member of the Turkish Biochemical Society, American Chemical Society, and German Genetics society. Dr. Ekinci published around ninety scientific papers, reviews and book chapters, and presented several conferences to scientists. He has received numerous publication awards from several scientific councils. Dr. Ekinci serves as the Editor in Chief of four international books and is involved in the Editorial Board of several international journals.",institutionString:null,institution:{name:"Ondokuz Mayıs University",institutionURL:null,country:{name:"Turkey"}}},editorThree:null},{id:"17",title:"Metabolism",coverUrl:"https://cdn.intechopen.com/series_topics/covers/17.jpg",isOpenForSubmission:!0,editor:{id:"138626",title:"Dr.",name:"Yannis",middleName:null,surname:"Karamanos",slug:"yannis-karamanos",fullName:"Yannis Karamanos",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002g6Jv2QAE/Profile_Picture_1629356660984",biography:"Yannis Karamanos, born in Greece in 1953, completed his pre-graduate studies at the Université Pierre et Marie Curie, Paris, then his Masters and Doctoral degree at the Université de Lille (1983). He was associate professor at the University of Limoges (1987) before becoming full professor of biochemistry at the Université d’Artois (1996). He worked on the structure-function relationships of glycoconjugates and his main project was the investigations on the biological roles of the de-N-glycosylation enzymes (Endo-N-acetyl-β-D-glucosaminidase and peptide-N4-(N-acetyl-β-glucosaminyl) asparagine amidase). From 2002 he contributes to the understanding of the Blood-brain barrier functioning using proteomics approaches. He has published more than 70 papers. His teaching areas are energy metabolism and regulation, integration and organ specialization and metabolic adaptation.",institutionString:null,institution:{name:"Artois University",institutionURL:null,country:{name:"France"}}},editorTwo:null,editorThree:null},{id:"18",title:"Proteomics",coverUrl:"https://cdn.intechopen.com/series_topics/covers/18.jpg",isOpenForSubmission:!0,editor:{id:"200689",title:"Prof.",name:"Paolo",middleName:null,surname:"Iadarola",slug:"paolo-iadarola",fullName:"Paolo Iadarola",profilePictureURL:"https://s3.us-east-1.amazonaws.com/intech-files/0030O00002bSCl8QAG/Profile_Picture_1623568118342",biography:"Paolo Iadarola graduated with a degree in Chemistry from the University of Pavia (Italy) in July 1972. He then worked as an Assistant Professor at the Faculty of Science of the same University until 1984. In 1985, Prof. Iadarola became Associate Professor at the Department of Biology and Biotechnologies of the University of Pavia and retired in October 2017. Since then, he has been working as an Adjunct Professor in the same Department at the University of Pavia. His research activity during the first years was primarily focused on the purification and structural characterization of enzymes from animal and plant sources. During this period, Prof. Iadarola familiarized himself with the conventional techniques used in column chromatography, spectrophotometry, manual Edman degradation, and electrophoresis). Since 1995, he has been working on: i) the determination in biological fluids (serum, urine, bronchoalveolar lavage, sputum) of proteolytic activities involved in the degradation processes of connective tissue matrix, and ii) on the identification of biological markers of lung diseases. 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