HEALTH AND DEVELOPMENT

We construct a cross-country dataset on female human capital inequality. Unlike the existing literature that primarily focuses on the average years of women's education, we use this dataset to examine the relationship between female human capital inequality and infant mortality. We show that higher education inequality among women, measured by the Gini coefficient, leads to substantially higher infant mortality. This finding is robust to various alternative specifications and subsamples considered. We also consider whether this channel is important in explaining growth. Growth regressions show favorable but weak evidence that education inequality among women is associated negatively with growth via its effect on infant mortality. Our main results have implications related to the policy question on the optimal allocation of educational subsidies. If infant mortality reduction is a priority for policy makers, then educating the least educated women first seems to be an effective (and also simple) policy recommendation.

We propose an economic theory of infectious disease transmission and rational behavior. Diseases are costly due to mortality (premature death) and morbidity (lower productivity and quality of life). The theory offers three main insights. First, higher disease prevalence implies lower saving-investment propensity. Preventive behavior can partially offset this when the prevalence rate and negative disease externality are relatively low. Secondly, infectious diseases can generate a low-growth trap where income alone cannot push an economy out of underdevelopment. This is distinctly different from development traps in the existing literature. Since income per se does not cause health in this equilibrium, successful interventions have to be health specific. Thirdly, a more favorable disease ecology propels the economy to a higher growth path where health and income co-evolve and infectious diseases disappear. Even so, diseases significantly slow down convergence. These results suggest the empirical relationship between health and income at the aggregate level may be more nuanced than realized.

This paper sheds new light on the impact of AIDS on cross-country income levels. We consider new UNAIDS/WHO data on officially reported AIDS cases for a panel of 89 countries over a 15 year period from 1986-2000 during which AIDS has spread across the world. These data are used to estimate cross-country level regressions employing panel data techniques. Our findings are as follows: First, when using the entire sample of countries we find that AIDS has a negative albeit marginally significant effect on the level of income. Second, when we control for regional effects we show that this negative effect is primarily driven by the sub-Sahara Africa and Latin America subsamples. Third, using AIDS data by age group, we find that the disease has a significantly negative impact on income only via infected people between the ages 16 and 34. Finally, while the economic impact of AIDS is negative and statistically significant, its economic significance measured by the estimated size of the AIDS coefficient is quite small.

Does medical technology originating in countries close to the technology frontier have a significant impact on health outcomes in countries distant from this frontier? This paper considers a framework where lagging countries may benefit from medical technology (a result of research and development by countries close to the frontier) that is embodied in medical imports or diffuses in the form of ideas. Using a novel dataset from a cross-section of 73 technology-importing countries, we show that medical technology diffusion is an important contributor to improved health status, as measured by life expectancy and mortality rates.

TECHNOLOGY, HUMAN CAPITAL AND GROWTH

This paper compares transitional dynamics in two alternative R&D non-scale growth models, one with endogenous human capital and the other without. We show that focusing on the asymptotic speed of convergence to discriminate between the two models' performance can be misleading. Our analysis suggests that a careful study of the entire adjustment paths predicted by alternative growth models starting far away from the balanced growth path is required in order to successfully discriminate among them.

This paper constructs an R&D non-scale growth model that includes endogenous human capital. The goal is to take the model's implications to the data once the complementarity between technology and human capital, commonly found in the empirical literature, is taken into account. Our model suggests that cross-sector labor movements induced by the complementarity between human capital and technology can be a key factor in replicating and explaining development experiences such as those of Japan and South Korea. In particular it is shown that the the adjustment paths of output growth, investment rates, interest rates, and labor shares implied by the proposed model are consistent with empirical evidence.

The growth literature has not yet established how data on education should be introduced in theories involving human capital. Early work used enrolment rates as a proxy of human capital whereas more recently it has utilized measures of average education al attainment taking advantage of new data sets. This paper examines alternative specifications of human capital that may match up with the existing data on education. First, we present a standard neoclassical two-sector growth model that adopts a human capital specification proposed in recent papers. In this model the fraction of individual's time endowment in school is viewed as an investment rate. We show that the optimally chosen educational attainment predicted by the calibrated model is very high and does not correspond to the data. Next, we consider two extensions of the basic model: (a) allow for different elasticities of substitution between skilled and unskilled labor, (b) introduce work experience. We find that neither of the two extensions are able to generate plausible predictions. Finally, we propose an alternative specification of human capital based on a law of motion of educational attainment that successfully matches up with the data.

This paper studies the transition dynamics predictions of an R&D-based growth model, and evaluates their performance in explaining income disparities across nations. We find that the fraction of the observed cross-country income variation explained by the transitional dynamics of the model is as large as the one accounted by existing steady-state level regressions. Our results suggest that the traditional view of a world in which nations move along their distinct balanced-growth paths is as likely as the one in which countries move along adjustment paths toward a common (very long-run) steady state.

This paper follows Benhabib and Spiegel (1994) in examining the effect of human capital accumulation on economic growth. The paper is innovative in two ways. First, it takes the R&D-based models more seriously. This delivers more structural specifications in which human capital affects growth as an input of final output and as a catalyst of technological innovation and imitation. Second, due to data availability it is possible to disaggregate human capital and assign different roles to primary and post-primary education. Regression estimates obtained from these alternative specifications suggest that the relative contribution of human capital to technology adoption and final output production vary by country wealth. More importantly, regression estimates suggest that primary education contributes mainly to production of final output, whereas post-primary education contributes mainly to adoption and innovation of technology.

Motivated by recent empirical evidence this paper extends a non-scale R&D growth model to allow for technological imitation in addition to innovation. It is shown that a simple modification of the standard R&D equation results in a more general model that can explain not only the growth process of developed countries that mostly innovate, but also the growth process of developing countries that mostly imitate.

This paper explores a model in which growth is determined by a combination of human capital and technology adoption. At the heart of the model is the notion of "contiguous knowledge" - the idea that knowledge spreads out a certain distance. Because of this property of knowledge, a developing country can adopt existing technology only when it is sufficiently close to the technological frontier. The nature of the model is optimistic in that technology gaps present an opportunity for developing countries that are relatively close to the frontier to achieve rapid growth through technology adoption. Unlike the neoclassical growth model however, the predictions of the model are rather pessimistic for countries that are far away from the frontier making them unable to take advantage of imitation. As a result, the model is able to account both for rapid growth episodes as well as economic stagnation.

COUNTRY HETEROGENEITY AND GROWTH

We construct a cross-country dataset on female human capital inequality. Unlike the existing literature that primarily focuses on the average years of women's education, we use this dataset to examine the relationship between female human capital inequality and infant mortality. We show that higher education inequality among women, measured by the Gini coefficient, leads to substantially higher infant mortality. This finding is robust to various alternative specifications and subsamples considered. We also consider whether this channel is important in explaining growth. Growth regressions show favorable but weak evidence that education inequality among women is associated negatively with growth via its effect on infant mortality. Our main results have implications related to the policy question on the optimal allocation of educational subsidies. If infant mortality reduction is a priority for policy makers, then educating the least educated women first seems to be an effective (and also simple) policy recommendation.

Economic growth has been a showcase of model uncertainty, given the many competing theories and candidate regressors that have been proposed to explain growth. Bayesian Model Averaging (BMA) addresses model uncertainty as part of the empirical strategy, but its implementation is subject to the choice of priors: the priors for the parameters in each model, and the prior over the model space. For a well-known growth dataset, we show that model choice can be sensitive to the prior specification, but that economic significance (model-averaged inference about regression coefficients) is quite robust to the choice of prior. We provide a procedure to assess priors in terms of their predictive performance. The Unit Information Prior, combined with a uniform model prior outperformed other popular priors in the growth dataset and in simulated data. It also identified the richest set of growth determinants, supporting several new growth theories. We also show that there is a tradeoff between model and parameter priors, so that the results of reducing prior expected model size and increasing prior parameter variance are similar. Our branch-and-bound algorithm for implementing BMA was faster than the alternative coin flip importance sampling and MC3 algorithms, and was also more successful in identifying the best model.

Trade theories covering Preferential Trade Agreements (PTAs) are as diverse as the literature in search of their empirical support. To account for the model uncertainty that surrounds the validity of the competing PTA theories, we introduce Bayesian Model Averaging (BMA) to the PTA literature. BMA minimizes the sum of Type I and Type II error, the mean squared error, and generates predictive distributions with optimal predictive performance. Once model uncertainty is addressed as part of the empirical strategy, we report clear evidence of Trade Creation, Trade Diversion, and Open Bloc effects. After controlling for natural trading partner effects, Trade Creation is weaker – except for the EU. To calculate the actual effects of PTAs on trade flows we show that the analysis must be comprehensive: it must control for Trade Creation and Diversion as well as all possible PTAs. Several prominent control variables are also shown to be robustly related to Trade Creation; they relate to factor endowments and economic policy.

We investigate the heterogeneous effects of initial conditions on post-World War II growth in sub- Saharan Africa. Our empirical strategy is based on Bayesian Model Averaging (BMA) that allows us to consider both model uncertainty (about the preferred theory and model) and parameter heterogeneity (that countries are not homogeneous objects) into an internally coherent estimation procedure. Our main ?nding is that the impact of initial conditions on subsequent growth in sub-Saharan Africa is distinct. How and why these initial conditions have a differential effect on this region is examined.

This paper takes a fresh look into Africa's growth experience by using the Bayesian Model Averaging (BMA) methodology. BMA enables us to consider a large number of potential explanatory variables and sort out which of these variable can effectively explain Africa's growth experience. Posterior coefficient estimates reveal that key engines of growth in Africa are substantially different from those in the rest of the world. More precisely, it is shown that mining, primary exports and initial primary education exerted differential effect on African growth. These results are examined in relation to the existing literature.

We investigate country heterogeneity in cross-country growth regressions. In contrast to the previous literature that focuses on low-income countries, this study also highlights growth determinants in high-income (OECD) countries. We introduce Iterative Bayesian Model Averaging (IBMA) to address not only potential parameter heterogeneity, but also the model uncertainty inherent in growth regressions. IBMA is essential to our estimation because the simultaneous consideration of model uncertainty and parameter heterogeneity in standard growth regressions increases the number of candidate regressors beyond the processing capacity of ordinary BMA algorithms. Our analysis generates three results that strongly support different dimensions of parameter heterogeneity. First, while a large number of regressors can be identified as growth determinants in Non-OECD countries, the same regressors are irrelevant for OECD countries. Second, Non-OECD countries and the global sample feature only a handful of common growth determinants. Third, and most devastatingly, the long list of variables included in popular cross-country datasets does not contain regressors that begin to satisfactorily characterize the basic growth determinants in OECD countries.

This paper uses a novel dataset to test the capital-skill complementarity hypothesis in a cross-section of countries. It is shown that for the full sample there exists evidence in favor of the hypothesis. When we arbitrarily split the full sample into OECD and non-OECD countries, we find no evidence in favor of the hypothesis for the OECD subsample, but strong evidence for the non-OECD subsample. When we use Hansen's (2000) endogenous threshold methodology we find that initial literacy rates and initial per capita output are threshold variables that can cluster countries into three distinct regimes that obey different statistical models. In particular, the regime with moderate initial per capita income but low initial education exhibits substantially higher capital-skill complementarity than the regime with low income and low education and the regime with high education. This cross-country nonlinearity in capital-skill complementarity is consistent with the time-series nonlinearity found by Goldin and Katz (1998) using U.S. manufacturing data, and promotes the view that the phenomenon maybe a transitory one.

This paper examines whether nonlinearities in the aggregate production function can explain parameter heterogeneity in the Solow (1956) growth regressions. Nonlinearities in the production technology are introduced by replacing the commonly used Cobb-Douglas (CD) aggregated production specification with the more general Constant-Elasticity-of-Substitution (CES) specification. We first justify our choice of production function by showing that cross-country level regressions favor the CES over the CD technology. Then, by using the endogenous threshold methodology of Hansen (2000) we show that the Solow model with CES technology is consistent with the existence of multiple regimes.

This paper employs the data-sorting method developed by Hansen (2000) which allows the data to endogenously select regimes using different variables. It is shown that openness, as measured by the trade share to GDP, is a threshold variable that can cluster middle-income countries into two distinct regimes that obey different statistical models. Our result suggests that openness may not be as crucial in the growth process of low and high-income countries but it is instrumental in identifying middle-income countries into high and low-growth groups.

AGGREGATE PRODUCTION TECHNOLOGY

The two-level CES aggregate production function - that nests a CES into another CES function - has recently been used extensively in theoretical and empirical applications of macroeconomics. We examine the theoretical properties of this production technology and establish existence and stability conditions of steady states under the Solow and Diamond growth models. It is shown that in the Solow model the sufficient condition for a steady state is fulfilled for a wide range of substitution parameter values. This is in sharp contrast with the two-factor Solow model, where only an elasticity of substitution equal to one is sufficient to guarantee the existence of a steady state. In the Diamond model, multiple equilibria can occur when the aggregate elasticity of substitution is lower than the capital share. Moreover, it is shown that for high initial levels of capital and factor substitutability, the effect of a further increase in a substitution parameter on the steady state depends on capital-skill complementarity.

In the literature studying aggregate economies the aggregate elasticity of substitution (AES) between capital and labor is often treated as a constant or "deep" parameter. This view contrasts with the conjecture put forward by Arrow et al. (1961) that AES evolves over time and changes with the process of economic development. This paper evaluates this conjecture in a simple dynamic multi-sector growth model, in which AES is endogenously determined. Our findings support the conjecture, and in particular demonstrate that AES tends to be positively related to the state of economic development, a result consistent with recent empirical findings.

We construct a one-sector growth model where the technology is described by a Variable Elasticity of Substitution (VES) production function. This framework allows the elasticity of factor substitution to interact with the level of economic development. First, we show that the model can exhibit unbounded endogenous growth despite the absence of exogenous technical change and the presence of non-reproducible factors. Second, we provide some empirical estimates of the elasticity of substitution, using a panel of 82 countries over a 28-year period, which admit the possibilities of a VES aggregate production function with an elasticity of substitution that is greater than one and consequently of unbounded endogenous growth.

Since Griliches (1969), researchers have been intrigued by the idea that physical capital and skilled labor are relatively more complementary than physical capital and unskilled labor. In this paper we consider the cross-country evidence for capital-skill complementarity using a time-series, cross-section panel of 73 developed and less developed countries over a 25 year period. We focus on three empirical issues. First, what is the best specification of the aggregate production technology to address the capital-skill complementarity hypothesis. Second, how should we measure skilled labor? Finally, is there any cross-country evidence in support of the capital-skill complementarity hypothesis? Our main finding is that we find some support for the capital-skill complementarity hypothesis in our macro panel dataset.

It is often asserted that the more substitutable capital and labor are in the aggregate production the more rapidly an economy grows. Recently this has been formally confirmed within the Solow model by Klump and de La Gradville (2000). This paper demonstrates that there exists no such monotonic relationship between factor substitutability and growth in the Diamond overlapping-generations model. In particular, we prove that, if capital and labor are relatively substitutable, a country with a greater elasticity of substitution exhibits lower per capital output and growth in transit and in steady state.

Many models of exogenous and endogenous growth assume that aggregate output is generated by a Cobb-Douglas specification for the aggregate production function with labor, physical capital, and sometimes human capital as inputs. In this paper we question the empirical relevance of the Cobb-Douglas specification. We consider new World Bank data on GDP, the labor supply, the stock of physical capital and educational attainment per worker for a panel of 82 countries over a 28 year period from 1960-87. These data are used to estimate a general CES production function specification for which the Cobb-Douglas specification is a special case. We find that for the entire 82 country-28 year panel we can reject a Cobb-Douglas specification for the aggregate production function. When we divide our sample of 82 countries up into several subsamples based on initial per capita income levels we find that we can continue to reject a Cobb-Douglas specification. In particular, we find that physical capital and human capital adjusted labor are more substitutable in the richest group of countries and less substitutable in the poorest group of countries than would be implied by a Cobb-Douglas specification. We discuss the implications of our findings for the debate concerning convergence in income levels across countries as well as for the plausibility of long-run endogenous growth due to the specification of the production technology.

MISCELLANEOUS

This chapter examines the relationship between the rapid pace of trade and financial globalization and the rise in income inequality observed in most countries over the past two decades. The analysis finds that technological progress has had a greater impact than globalization on inequality within countries. The limited overall impact of globalization reflects two offsetting tendencies: whereas trade globalization is associated with a reduction in inequality, financial globalization—and foreign direct investment in particular— is associated with an increase in inequality. It should be emphasized that these findings are subject to a number of caveats related to data limitations, and it is particularly difficult to disentangle the effects of technology and financial globalization since they both work through processes that raise the demand for skilled workers. The chapter concludes that policies aimed at reducing barriers to trade and broadening access to education and credit can allow the benefits of globalization to be shared more equally.

This paper discusses the relationship between economic development and one aspect of property rights, a statute of limitations defining time limits on ownership claims. The analysis centers on property rights in land. This paper argues that the available development opportunities shape the time limits on ownership claims that maximize property values, which in turn creates an inherent underlying tension among the owners of different types of property in the economy. An implication for positive analysis is that economic growth and successful development create demands for changing this dimension of property rights. Other characteristics of the economy like the efficiency of the legal system, the quality of the public sector bureaucracy, and corruption, also affect the value-maximizing time limitations for different types of property. This paper discusses implications of these relationships for developing countries and for property redevelopment in declining central cities in the US.

This paper reports findings of an experiment motivated by a dynamic labor market model that considers the problem faced by an employer in making hiring decisions of workers of different types. The question examined here is how quickly do employers learn about workers ability through observing the their performance in the workplace. If prior opinions are weak, the employer will quickly update any group-based stereotypes with information from the workplace. Our experimental findings are twofold: first subjects (employers) learn fast and second priors are hard to establish.

One of the main issues associated with recent R&D-based growth models is their prediction concerning "scale effects". That is, these models ask the question as to whether economic growth is a function of the level or the growth rate of human capital at steady state. This note presents some cross-country and historical time series evidence that supports scale effects in the early stages of development and non scale effects in the long-run.

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