Complex Economies Have a Lateral Escape from the Poverty Trap (original) (raw)
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Brazilian Journal of Political Economy, 2018
This paper brings elements from the economic complexity literature to the discussions of the structuralist tradition on the central role of manufacturing and productive sophistication to economic growth. Using data provided by the Atlas of Economic Complexity this study sought to verify if countries’ complexity is important to explain convergence and divergence among poor and rich countries and, if so, which are the countries that will be able to reduce the income gap compared to developed countries. The econometric analysis revealed that exports and production complexity is significant to explain convergence and divergence among countries.
Economic Complexity and Sustainable Growth in Developing Countries
Economics Development Analysis Journal, 2022
Most developing countries in this study are middle to low-income countries that have a relatively low economic complexity. This study aims to analyze the effect of the economic complexity on economic growth in 86 developing countries in 2010-2019. The method used is the Generalized Method of Moments (GMM) to capture dynamic panel analysis. The estimation results using the System GMM show that economic complexity has a positive effect on economic growth in developing countries. Increasing economic complexity encourages a structural transformation through high value-added economic sectors' creation to produce more complex products for earning a higher income. Human capital does not have a significant effect on economic growth because developing countries have relatively low-quality workers both in terms of education and health. The human capital development and government spending on the health sector are necessary to accelerate sustainable economic growth.
Reconciling contrasting views on economic complexity
Nature Communications, 2020
Summarising the complexity of a country’s economy in a single number is the holy grail for scholars engaging in data-based economics. In a field where the Gross Domestic Product remains the preferred indicator for many, economic complexity measures, aiming at uncovering the productive knowledge of countries, have been stirring the pot in the past few years. The commonly used methodologies to measure economic complexity produce contrasting results, undermining their acceptance and applications. Here we show that these methodologies – apparently conflicting on fundamental aspects – can be reconciled by adopting a neat mathematical perspective based on linear-algebra tools within a bipartite-networks framework. The obtained results shed new light on the potential of economic complexity to trace and forecast countries’ innovation potential and to interpret the temporal dynamics of economic growth, possibly paving the way to a micro-foundation of the field.
Economic complexity to boost the selected sub-Saharan African economies
Journal of Economic and Financial Sciences, 2021
Orientation: Economic complexity is a measure of productive capabilities indirectly by looking at the mix of sophisticated products that countries export. The economic complexity index proposed a proxy for diversity and ubiquity of products in the export basket. Research purpose: This study seeks to determine if economic complexity can influence the inequality measured by the Gini index in some selected sub-Saharan African countries. Motivation for the study: The need for the study emanates from the notion that that economic complexity can reduce income inequality hence it is imperative to investigate this relationship in the sub-Saharan African region where most countries produce few sophisticated goods that are also labour-intensive. Inadequate literature within the African continent has also contributed to the formulation of this study. Research approach/design and method: This study employed the autoregressive distribution lag (ARDL) model to analyze a panel data set, which incl...
The building blocks of economic complexity
In ref. 4, Maddison presents GDP per capita measures for 60 countries since 1820. In that year, the ratio of the 95th to the 5th percentile was 3.18 but it increased to 17.82 by the year 2000. Today, the U.S. GDP per capita is Ͼ60 times higher than Malawi's. This article contains supporting information online at www.pnas.org/cgi/content/full/ 0900943106/DCSupplemental.
Production complexity, adaptability and economic growth
Structural Change and Economic Dynamics, 2016
This paper analyzes the impact of production complexity and its adaptability on the level of output and on its rate of growth. We develop an endogenous growth model where increased complexity raises the rate of economic growth but has an ambiguous effect on the level of output. Our empirical measure of production adaptability captures the proximity of production sectors within the product space, which we modify to reflect intra-industry trade and the international fragmentation of production. We test the model against a sample of 89 countries over the two decades to 2009 and find that its main predictions are validated.
Linking Economic Complexity, Institutions, and Income Inequality
A country's mix of products predicts its subsequent pattern of diversification and economic growth. But does this product mix also predict income inequality? Here we combine methods from econometrics, network science, and economic complexity to show that countries exporting complex products-as measured by the Economic Complexity Index-have lower levels of income inequality than countries exporting simpler products. Using multivariate regression analysis, we show that economic complexity is a significant and negative predictor of income inequality and that this relationship is robust to controlling for aggregate measures of income, institutions, export concentration, and human capital. Moreover, we introduce a measure that associates a product to a level of income inequality equal to the average GINI of the countries exporting that product (weighted by the share the product represents in that country's export basket). We use this measure together with the network of related products-or product space-to illustrate how the development of new products is associated with changes in income inequality. These findings show that economic complexity captures information about an economy's level of development that is relevant to the ways an economy generates and distributes its income. Moreover, these findings suggest that a country's productive structure may limit its range of income inequality. Finally, we make our results available through an online resource that allows for its users to visualize the structural transformation of over 150 countries and their associated changes in income inequality during 1963-2008.
The role of complex analysis in modeling economic growth
RePEc: Research Papers in Economics, 2018
Development and growth are complex and tumultuous processes. Modern economic growth theories identify some key determinants of economic growth. However, the relative importance of the determinants remains unknown, and additional variables may help clarify the directions and dimensions of the interactions. The novel stream of literature on economic complexity goes beyond aggregate measures of productive inputs and considers instead a more granular and structural view of the productive possibilities of countries, i.e., their capabilities. Different endowments of capabilities are crucial ingredients in explaining differences in economic performances. In this paper we employ economic fitness, a measure of productive capabilities obtained through complex network techniques. Focusing on the combined roles of fitness and some more traditional drivers of growth-GDP per capita, capital intensity, employment ratio, life expectancy, human capital and total factor productivity-we build a bridge between economic growth theories and the economic complexity literature. Our findings show that fitness plays a crucial role in fostering economic growth and, when it is included in the analysis, can be either complementary to traditional drivers of growth or can completely overshadow them. Notably, for the most complex countries, which have the most diversified export baskets and the largest endowments of capabilities, fitness is complementary to the chosen growth determinants in enhancing economic growth. The empirical findings are in agreement with neoclassical and endogenous growth theories. By contrast, for countries with intermediate and low capability levels, fitness emerges as the key growth driver. This suggests that economic models should account for capabilities; in fact, describing the technological possibilities of countries solely in terms of their production functions may lead to a misinterpretation of the roles of factors.
Structural change and economic dynamics: Rethinking from the complexity approach
Journal of Dynamics & Games, 2019
Economic systems have evolved through time thereby changing the structure that characterizes them. These changes respond to technological changes that transform economies into highly interconnected systems. The modifications in the norms that guide the behaviour of organizations and, therefore the functioning of the economy, are a first case of this transformation. The industrialization process, through the incorporation of increasing returns to scale in different sectors, and the introduction of service activities are other examples. Another form to represent structural change is the change of the values of the variables that characterize the state space of an economic system. This research article is an effort to put together and compare, from the complexity approach, different approaches for structural change and dynamics of economic systems. We start by briefly presenting the complexity approach in general and in economics. Then, we put forward three approaches highlighting structural change.
Economic complexity, human capital and income inequality: a cross-country analysis
The Japanese Economic Review
This paper investigates the relationship between economic complexity, a measure of economic structures, and income inequality. Using a crosscountry OLS regression, we show that countries with economic structures geared toward complex products enjoy a lower level of inequality. Human capital is found to magnify this correlation. Different measures of human capital also have differentiated interaction effects. Concerns about the endogeneity bias of OLS estimates motivate us to estimate a dynamic panel data model, using a system GMM estimator. We find that an increase in economic complexity provokes higher inequality.