Economic Growth Nonlinearities

Nonlinearities in growth have important implications for cross-country income inequality. In particular, they imply that countries may spend long periods of time in a low-growth poverty trap. However, finding evidence of such nonlinearities in the data and accounting for their emergence pose unique challenges to researchers.

Understanding Preferences For Income Redestribution

Recent research suggests that income redistribution preferences vary across identity groups. We employ a new pattern recognition technology, tree regression analysis, to uncover what these groups are. Using data from the General Social Survey, we present a new stylized fact that preferences for governmental provision of income redistribution vary systematically with race, gender, and class background. We explore the extent to which existing theories of income redistribution can explain our results, but conclude that current approaches do not fully explain the findings.

Understanding Divergent Views on Redistribution Policy in the United States

Particular demographic groups are often associated with distinct points of view across various dimensions of redistribution policy. In this paper, we investigate which demographic groups account for heterogeneity in views on welfare policy and views on appropriate levels of overall redistribution. Using data from the General Social Survey and classification tools, we find evidence that classifications of the population by race, socioeconomic status, and age have some predictive power. However, much heterogeneity in views on redistribution policy persists even within these demographic groupings and remains unexplained. Our results suggest that identity-based explanations for variations in these views have to be interpreted with caution.Data mining, classification and regression trees, random forests, redistribution preferences, welfare, identity

Do institutions rule? The role of heterogeneity in the institutions vs. geography debate

We uncover evidence of substantial heterogeneity in the growth experience of countries using a structural threshold regression methodology. Our findings suggest that studies that seek to promote mono-causal explanations in the institutions versus geography debate in growth are potentially misleadingThreshold Regression, Endogenous Threshold Variables, Growth, Institutions, Geography.

No One True Path: Uncovering the Interplay between Geography, Institutions, and Fractionalization in Economic Development

Do institutions “rule” when explaining cross-country divergence? This paper finds that to a large extent they do. However, the role of ethno-linguistic fractionalization cannot be ignored. Sufficiently high-quality institutions are necessary if the negative impact on development from high levels of ethno-linguistic fractionalization is to be mitigated. Interestingly, I find no role for geographic factors; neither those associated with climate nor geographic isolation, in explaining divergence. There is also no evidence to suggest a role for religious fractionalization. Finally, my findings affirm earlier work in the literature that sets apart Sub-Saharan Africa’s development process from the rest of the world.Regression Trees, Economic Growth, Fundamental Determinants

Failure to Launch? The Role of Land Inequality in Transition Delays

Recent work in the growth literature has provided various explanations for transition delays and the great divergence. This paper provides empirical support for one theory of transition delays: initial land inequality. Our analysis is designed to elucidate the channels via which land inequality can affect long-run economic performance. Using a new historical data set for land inequality (Frankema (2009)) we employ duration analysis to investigate whether higher levels of land inequality lead to longer delays in the extension of primary schooling. We then investigate whether such delays affect long-run economic performance via their effect on contemporaneous schooling. Our findings suggest that land inequality is a key determinant of delays in schooling, and that such delays have a significant negative impact on long-run output.growth takeoffs, schooling, duration analysis, model uncertainty, institutions.

Do Institutions Rule? The Role of Heterogeneity in the Institutions vs. Geography Debate

We uncover evidence of substantial heterogeneity in the growth experience of countries using a structural threshold regression methodology. Our findings suggest that studies that seek to promote mono-causal explanations in the institutions versus geography debate in growth are potentially misleading.Threshold Regression, Endogenous Threshold Variables, Growth, Institutions, Geography

Structural Threshold Regression

This paper extends the simple threshold regression framework of Hansen (2000) and Caner and Hansen (2004) to allow for endogeneity of the threshold variable. We develop a concentrated least squares estimator of the threshold parameter based on an inverse Mills ratio bias correction. We show that our estimator is consistent and investigate its performance using a Monte Carlo simulation that indicates the applicability of the method in finite samples.

Structural Threshold Regression

This paper introduces the structural threshold regression model that allows for an endogeneous threshold variable as well as for endogenous regressors. This model provides a parsimonious way of modeling nonlinearities and has many potential applications in economics and finance. Our framework can be viewed as a generalization of the simple threshold regression framework of Hansen (2000) and Caner and Hansen (2004) to allow for the endogeneity of the threshold variable and regime specific heteroskedasticity. Our estimation of the threshold parameter is based on a concentrated least squares method that involves an inverse Mills ratio bias correction term in each regime. We derive its asymptotic distribution and propose a method to construct bootstrap confidence intervals. We also provide inference for the slope parameters based on GMM. Finally, we investigate the performance of the asymptotic approximations and the bootstrap using a Monte Carlo simulation that indicates the applicability of the method in finite samples.

Is the Relationship Between Aid and Economic Growth Nonlinear?

In this paper, we investigate the relationship between foreign aid and growth using recently developed sample splitting methods that allow us to uncover evidence for the existence of heterogeneity and nonlinearity simultaneously. We also implement a new methodology that allows us to deal with model uncertainty in the context of these methods. We find some evidence that aid may have heterogeneous effects on growth across two growth regimes defined by ethnic fractionalization. In particular, countries that belong to a growth regime characterized by levels of ethnic fractionalization above a threshold value experience a negative partial relationship between aid and growth, while those in the regime with ethnic fractionalization below the threshold experience no growth effects from aid at all. Nevertheless, there exists substantial model uncertainty so that attempts to pin down the typology of these growth regimes as being decisively characterized by ethnic fractionalization remain inconclusive. When we account for model uncertainty, we find no evidence to suggest that the relationship between aid and growth is nonlinear. Overall, our results suggest that the partial effect of aid on growth is very likely to be negative although we cannot reject the hypothesis that aid has no effect on growth. In this sense, our findings suggest that aid is potentially counterproductive to growth with outcomes not meeting the expectations of donors.