STRUCTURAL TRANSFORMATION AND ECONOMIC DEVELOPMENT Can Development Traps be Avoided? Alejandro Martín Lavopa - PDF

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STRUCTURAL TRANSFORMATION AND ECONOMIC DEVELOPMENT Can Development Traps be Avoided? Alejandro Martín Lavopa copyright Alejandro Martín Lavopa, Maastricht 2015 Cover Picture: M.C. Escher, Relativity. All

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STRUCTURAL TRANSFORMATION AND ECONOMIC DEVELOPMENT Can Development Traps be Avoided? Alejandro Martín Lavopa copyright Alejandro Martín Lavopa, Maastricht 2015 Cover Picture: M.C. Escher, Relativity. All M.C. Escher works 2015 The M.C. Escher Company - the Netherlands. All rights reserved. Used by permission. Printing: Datawyse Universitaire Pers Maastricht ISBN Structural Transformation and Economic Development. Can Development Traps be Avoided? DISSERTATION to obtain the degree of Doctor at Maastricht University, on the authority of the Rector Magnificus, Prof. Dr. L.L.G. Soete in accordance with the decision of the Board of Deans, to be defended in public on Thursday 12 March 2015, at hours by Alejandro Martín Lavopa UUNIVERSITAIRE PERS MAASTRICHT P M Supervisors: Prof. Dr. Adam Szirmai Prof. Dr. Bart Verspagen Assessment Committee: Prof. Dr. Robin Cowan (Chair) Dr. Marco Capasso Prof. Dr. Giovanni Dosi (Sant Anna School of Advanced Studies, Pisa) Prof. Dr. Marcel Timmer (Groningen University) CONTENTS ACKNOWLEDGMENTS... i SUMMARY... v CHAPTER 1. Introduction The Elusive Road to Economic Development Structural Change and Technological Upgrading Research Approach Structure of the Book... 5 CHAPTER 2. Literature Review Introduction Economic Growth and Development Traps Technological Gaps and the Dual Economy Sectoral Engines of Growth Specialization Patterns and Economic Development Final Remarks CHAPTER 3. Technological Catch Up in a Balance-of-Payments Constrained Dual Economy Introduction The Model Dynamical Behaviour Trajectories and Development Traps Final Remarks CHAPTER 4. Structural Modernisation and Development Traps Introduction Empirical Approach Structural Change and Development Development Traps Structural Trajectories Final Remarks CHAPTER 5. Structural Modernisation, Trade Specialization and Economic Growth. The Role of Manufacturing Introduction Structural Modernisation and Economic Growth Export Structure and Economic Growth Final Remarks CHAPTER 6. Sectoral Heterogeneities and Structural Change in the Modern Sector Introduction Data Structural Characterization Patterns of Structural Change Sectoral Contributions Final Remarks CHAPTER 7. Conclusions Research Findings Policy Implications Limitations and Further Research REFERENCES APPENDIX A. Appendix to Chapter A.1. Viability Conditions A.2. Stability Properties A.3. Comparative statics APPENDIX B. Appendix to Chapter B.1. Defining the Development Traps APPENDIX C. Appendix to Chapter C.1. Regression Results (Figure 5.2 and Figure 5.3) C.2. Robustness Checks APPENDIX D. Appendix to Chapter D.1. Catch-up Decomposition APPENDIX E. Constructing the Dataset E.1. Per capita GNI E.2. Sectoral Employment and Value Added E.3. Unemployment E.4. Other Variables E.5. Sources Used and Period Covered VALORISATION SAMENVATTING BIOGRAPHY LIST OF TABLES Table 3.1. Definition and interpretation of each term in the dynamic system Table 3.2. Equilibrium points Table 3.3. Viability conditions Table 3.4. Viability conditions under different restrictions on the signs of A, D and the slope differential Table 3.5. Stability properties of the equilibria under different cases Table 3.6. Comparative statics in the vicinity of Equilibrium 4 (sign of the partial derivatives with respect to the deep parameters of the model) Table 4.1. Sectoral disaggregation and definition of Modern Market Activities (MMA) Table 4.2. Transition matrix for countries that have successfully improved their income category between and are unlikely to be in the middle-income trap. 52 countries Table 4.3. Countries in a development trap. 2013, 30 countries Table 4.4. Countries in a development trap by regions of the structural modernization landscape countries Table 4.5. Typology of countries based on the regions of the structural modernization landscape Table 5.1. Descriptive statistics of the panel dataset Table 5.2. Hausman s (1978) specification test for the explanatory variables Table 5.3. Determinants of growth. The role of modern market activities. Hausman-Taylor estimates for the period Table 5.4. Determinants of growth: the effect of MMA composition including interactions with explanatory variables , Hausman-Taylor estimates Table 5.5. Classification of Manufacturing exports by technology intensity Table 5.6. Classification of Manufacturing exports by average level of income elasticity Table 5.7. Descriptive statistics. Trade variables Table 5.8. Hausman s (1978) specification test for the explanatory trade variables Table 5.9. Determinants of growth. The role of exports Table Determinants of growth: the role of different manufacturing value added exports groups Table 6.1. Sectoral disaggregation within Modern Market Activities Table 6.2. Sub-sample of countries analysed in this chapter Table 6.3. Relative labour productivity (world frontier = 100) in MMA and sectoral dispersion, by country. 5-year averages around Table 6.4. Sectoral productivity in the world leader (United States). Absolute and relative levels. 5- year averages around 1972 and Table 6.5. Decomposition results. First period ( ). Percentage points of the aggregate growth rate in MMA relative productivity Table 6.6. Decomposition results. Second period ( ) Percentage points of the aggregate growth rate in MMA relative productivity Table 6.7. Decomposition results: concentration degree of the catching up process and Table 6.8. Annual growth rates of the structural modernisation index, the relative productivity of MMA and the share of MMA workers in total labour force, by country and sub-period (in percentages) Table A. 1. Cases in which VC1 and VC2 are satisfied Table A. 2. Cases in which VC3 and VC4 are satisfied Table A. 3. VC1 and VC2 in Case Table A. 4. VC1 and VC2 in Case 1 (in terms of slopes and intercepts) Table A. 5. VC3 and VC4 in Case 1 (in terms of slopes and intercepts) Table A. 6. VC1 and VC2 in Case 2 (in terms of slopes and intercepts) Table A. 7. VC3 and VC4 in Case 2 (in terms of slopes and intercepts) Table A. 8. Trace and determinant of the Jacobian for each equilibria Table A. 9. Trace and determinant signs and stability properties of the equilibria in each sub-case Table A. 10. Partial derivatives in terms of A, B, C, D, E and F with respect to the deep parameters of the model Table B. 1. Economies that turned to lower-middle incomes (LMI) after 1950 and graduated to upper-middle incomes (UMI) before countries Table B. 2. Economies that turned to upper-middle incomes (UMI) after 1950 and graduated to high incomes (HI) before countries Table B. 3. Characterization of middle-income economies (MIEs). 40 countries Table B. 4. Projected number of years needed by the low-income economies (LIEs) of our sample to turn into lower-middle-income economies (LMIE), given the growth rate of the last 20 years. 23 countries Table C. 1. Determinants of growth: manufacturing value added exports by technology intensity groups interacted with relative productivity in manufacturing Table C. 2. Determinants of growth: manufacturing value added exports by technology intensity groups interacted with relative productivity in manufacturing Table C. 3. Hausman s (1978) specification test for the models estimated in the chapter Table C. 4. Robustness check: the effect of alternative measures for the key variables of Model Table C. 5. Robustness check: the effect of an alternative specification for the composition of the modern sector Table C. 6. Robustness check: the effect of sectoral composition by income level Table E. 1. Additional sources for sectoral employment Table E. 2. Sources used and period covered by country: Per capita GNI Table E. 3. Sources used and period covered by country: Sectoral Employment and Value Added Table E. 4. Sources used and period covered by country (Latin American countries): Unemployment rate Table E. 5. Sources used and period covered by country (non-oecd, Asian and African countries): Unemployment rate Table E. 6. Manufacturing value added exports. Sources and coverage by country LIST OF FIGURES Figure 3.1. Graphical representation of the equilibria Figure 3.2. Graphical representation of the different cases Figure 3.3. Illustrative trajectories under different stability properties in Eq Figure 3.4. Initial stage Figure 3.5. Big-push on technological investments Figure 3.6. Emergence of a modern exporting sector Figure 3.7. Path towards successful development Figure 3.8. Acceleration of global technological change and real appreciation of the domestic currency Figure 4.1. Structural Modernization Landscape: Level curves and structural trajectories Figure 4.2. Share of labour force in Modern Market Activities (MMA) and Industry by levels of per capita Gross National Income (GNI), at constant PPP dollars of Five year averages between 1950 and 2009 for 97 countries Figure 4.3. Relative labour productivity in Modern Market Activities (MMA) by levels of per capita Gross National Income (GNI), at constant PPP dollars of Five year averages between 1950 and 2009 for 97 countries Figure 4.4. Structural modernization index by levels of per capita Gross National Income (GNI), at constant PPP dollars of Five year averages between 1950 and 2009 for 97 countries Figure 4.5. Structural modernization index by levels of per capita GNI at constant PPP dollars of Average values between 2005 and 2009 for countries in low or middle-income traps Figure 4.6. Structural modernization landscape. Average values between 2005 and 2009 for high income countries and countries in a development trap Figure 4.7. Structural trajectories (five year averages). Rep. of Korea and Taiwan Figure 4.8. Structural trajectories (five year averages). Hong Kong and Singapore Figure 4.9. Structural trajectories (five year averages). China and Thailand Figure Structural trajectories (five year averages). Brazil and South Africa Figure Structural trajectories (five year averages). Bolivia and Philippines Figure Structural trajectories (five year averages). Ethiopia and Tanzania Figure 5.1. Marginal effect of different explanatory variables on growth, when interacted with share of Manufacturing in MMA Figure 5.2. Marginal effect of manufacturing value added exports in different technology intensity groups, by level of relative productivity in manufacturing Figure 5.3. Marginal effect of manufacturing value added exports in different income elasticity groups, by level of relative productivity in manufacturing Figure 6.1. Distribution of labour by sectoral technological gaps Figure 6.2. Distribution labour by sectoral technological gaps Figure 6.3. Stylized trajectories in the distribution of labour by sectoral technological gaps Figure 6.4. Productivity at the frontier (millions of 2005 international dollars). By sector, (5yr averages) Figure 6.5. Relationship between sectoral heterogeneity and technological catching up. 30 countries, 5- year average around Figure 6.6. Distribution of labour by sectoral relative productivity. India and the United States, 5- year averages around Figure 6.7. Distribution of labour by sectoral relative productivity in successful mature high-income economies. 5-year averages around 1972, 1982 and Figure 6.8. Distribution of labour by sectoral relative productivity in successful newly high-income economies. 5-year averages around 1972, 1982 and Figure 6.9. Distribution of labour by sectoral relative productivity in countries trapped at middle incomes. 5-year averages around 1972, 1982 and Figure Distribution of labour by sectoral relative productivity at the frontier. Brazil, India and the United States, 5-year averages around Figure Distribution of labour by sectoral relative productivity at the frontier in Korea, 5- year averages around 1972, 1982 and Figure Harberger diagram Figure B. 1. Distribution of countries according to the number of years they needed to graduate from lower-middle income (LMI) to upper-middle income (UMI) category Figure B. 2. Distribution of countries according to the number of years they needed to graduate from upper-middle income (UMI) to high income (HI) category Figure B. 3. Distribution of low income countries (LICs) according to the projected number of years they will need to graduate to the lower-middle income (LMI) category i ACKNOWLEDGMENTS Any piece of new knowledge is the result of collaborative thinking, and this thesis is certainly not an exception. For this reason, I would like to use the first pages of this book to acknowledge all the people who contributed in the development of this thesis. First and foremost, I would like to thank my promoter and supervisor, Eddy Szirmai, for his constant guidance and encouragement throughout the Phd process. Besides being an excellent supervisor, always ready to give me his advice on the many issues and problems that aroused during this research, he has definitely shaped my approach to doing research in a way that will go far beyond this thesis. After these years working with him I have learnt to be as rigorous as possible and back all my statements with solid empirical evidence. I am also grateful for his full trust on me and the many opportunities he gave me to collaborate in different research projects. My involvement in these projects not only broadened my perspective on key economic development issues but also opened many doors for my future professional career. I would also like to thank my co-supervisor, Bart Verspagen, who has guided me into a completely unexplored area: the art of economic modeling. The theoretical foundations of this thesis would have certainly been less solid without his sharp advice. Our meetings to discuss the theoretical model have been invaluable learning experiences that I have very much appreciated. The thesis has also greatly benefited from the excellent comments and suggestions of the member of the assessment committee: Robin Cowan, Marco Capasso, Giovani Dosi and Marcel Timmer. Their comments gave new ideas and helped me to improve some weak points of the thesis. I could not, however, make justice to all their thoughtful points. Many of these suggestions, in fact, will remain fertile ground of though for my future research. My research has also been shaped and improved by fruitful debates and talks with my fellow PhD students and researchers from UNU-MERIT and Maastricht University. To begin with, I had benefited from an outstanding cohort of colleagues with whom I have shared not only inspiring discussions (inside and outside the institute) but also extremely beautiful moments. So I want to deeply thank Daniel O., François, Giorgio, Jocelyn, Samyukta, Sayan and Tatevik for being the best batch ever and Francesca and Jennifer T. for being the best adopted mates! Besides them I also had the pleasure to meet and share great experiences with many other students and researchers. The list is large, so here I will only mention some of them. Thanks to you all for sharing these years with me: Agustín, Alejandro, Alison, Andrea, Andrés, Andy, Charlotte, Claudio, Craig, Daniel V., Eduardo, Elisa, Ezequiel, ii ACKNOWLEDGMENTS Francisco, Iman, Irina, Jennifer W., Jojo, Juan Carlos, Julieta, Lilia, Luciana, Mary, Michiko, Omar, Paula, Paulina, Rodolfo, Shuan, Simone, Stefania F., Stefania I. and Tobias. Even though most of this thesis has been developed and written in Maastricht, it has also benefited from close collaborations with other researchers from different corners of the world. Among them, I would like to specially thank Mario Cimoli, Gabriel Porcile and the other members of the Division of Production, Productivity and Management of ECLAC. The thesis has greatly benefited from my research visit there in 2012 which brought me much closer to the theoretical insights and empirical analysis of the Latin American Structuralism. I am also grateful to Ludovico Alcorta, Nobuya Haraguchi, Michele Clara, Nicola Cantore and the other members of the Development Policy, Statistics and Research Branch of UNIDO. My collaboration in different projects of this research team and my direct involvement in the Industrial Development Report 2014 put me in closer contact with the current debate on the role of manufacturing and industrialization in economic growth and the main challenges faced by low and middle income economies in their path towards development. Finally, I would like to thank Marcel Timmer, Gaaitzen de Vries, Bart Los and the other members of the research team of the Groningen Growth and Development Center (GGDC) for giving me extremely helpful comments and suggestion at different stages of my Phd research and for providing me invaluable help in the construction of my dataset. The empirical chapters of this thesis would certainly not be as comprehensive as they are now without your thoughtful advice and the many dataset you have been producing in the last years. This research has also benefited from comments and suggestions at different conferences and workshops around the world: Tampere, Buenos Aires, Brisbane, Sao Paulo and Addis Ababa. From these experiences I would like to specially thank the enlightening comments and suggestions of Jorge Katz, Franco Malerba, Jorge Niosi, Chan Yuan Wong and Mercedes Campi. Coming from abroad, it has not always been easy to adapt to a completely new environment, kilometers away from home. This adaptation would have definitely not been as smooth if Eveline had not been around supporting me in every stage of my research. My most sincere thank for all the efforts she daily makes to transform the institute in our second home. Your efforts definitely make a difference. I would also like to express my gratitude to the other staff members that make UNU-MERIT such a lovely place to conduct research: Ad, Eric, Herman, Howard, Marc, Mitie, Mourik and Wilma. Being a long journey, this thesis had also a starting point, and it would have never been possible without the strong support of some people back in Argentina. I would like to thank specially to Alberto Müller, Javier Lindenboim and Daniel iii Heymann for their kind support back in the days in which doing a Phd abroad was just an ambitious and loosely defined project. I would also like to acknowledge the fundamental role played by the University of Buenos Aires in my academic formation. A completely free and public University with such level of excellence is a precious privilege that I, as Argentinean, had the opportunity to enjoy. I hope that this piece of research is a good reflection of it. Finally, I would like to dedicate this thesis to my closest ones and my family back in Argentina. A mis mejores amigos, Chris, Fede y Juan, siempre listos para hablar a la distancia y hacer desaparecer cualquier tipo de nostalgia a lo largo de estos años; a mi familia, Fede, Linda y Renu, siempre recordándome la calidez del hogar; y a Francesca, my compañera más cercana y mi punto de referencia más claro en este largo viaje. A todos ustedes mi más profundo agradecimiento por estar siempre ahí, al lado mío, apoyándome en cada paso que di para terminar esta tesis. v SUMMARY The main goal of this thesis is to investigate economic development as a process of structural transformation. In particular, the thesis postulates that there are two key transformations that need to be achieved in order to catch up with the advanced world: on one hand, the absorption of an increasing share of the labour force in the modern part of the economy (structural change); on the other hand, the technological upgrading of these modern sectors (technological catch up). Failure to achieve either of these transformations will eventually lead to low- or middleincome traps, in which only a fraction of the society can reap the benefits of the international flows of technological knowledge. This general hypothesis is grounded in a series of theoretical contributions that, from different perspectives, have acknowledged the fundamental role of structural change
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