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This paper uncovers novel empirical patterns in the cross-country price mechanism using a nonlinear factor model and threshold regression analysis based on individual goods retail price data for a large panel of countries. To our knowledge, this is the first paper to find strong evidence for club convergence of retail prices. These clubs emerge due to the interaction of traded and nontraded factors. For example, countries physically closer to potential trade partners converge faster than countries in the high distance regime as long as they have low initial labor productivity or low initial income. Moreover, we find an asymmetry in the extent that arbitrage opportunities related to international trade are exploited, with low initial price regime countries exhibiting faster convergence from below than high initial price regime countries exhibit from above, consistent with less resistance to exporting than to importing due to political economy considerations. We interpret our findings as evidence of a local law of one price due to barriers to price convergence influencing the duration of the effect of price shocks. 33 7 1081 1097

In this article, we explore nonlinearities in the intergenerational mobility process using threshold regression models. We uncover evidence of threshold effects in children's outcomes based on parental education and cognitive and noncognitive skills as well as their interaction with offspring characteristics. We interpret these thresholds as organizing dynastic earning processes into “status traps.” Status traps, unlike poverty traps, are not absorbing states. Rather, they reduce the impact of favorable shocks for disadvantaged children and so inhibit upward mobility in ways not captured by linear models. Our evidence of status traps is based on three complementary datasets that is, the PSID, the NLSY, and US administrative data at the commuting zone level, which together suggest that the threshold-like mobility behavior we observe in the data is robust for a range of outcomes and contexts. © 2017 American Statistical Association. 35 265 287 265-287

We employ a structural threshold regression methodology to investigate the heterogeneous effects of debt on growth using public debt as a threshold variable as well as several other plausible variables. Our methodology allows us to address parameter heterogeneity that characterizes cross-country growth data and at the same time account for endogeneity. We find strong evidence for threshold effects based on democracy, which implies that higher public debt results in lower growth for countries in the Low-Democracy regime. Our results are consistent with the presence of parameter heterogeneity in the cross-country growth process due to fundamental determinants of economic growth proposed by the new growth theories. © 2013 Elsevier Inc. 38 35 43 35-43

This paper investigates the presence of multiple regimes in the preferences of redistribution, which is a key feature of a welfare state. The size of the redistributive government depends on the demand for redistribution, that is, the willingness of individuals to tax the rich more heavily and transfer resources to the poor. Surprisingly, while several theories imply nonlinear models (e.g., Piketty (1995), Benabou (2000), Benabou and Ok (2001), Alesina and Angeletos (2005)), the existing empirical work (e.g., Alesina and La Ferrara (2005), Alesina and Giuliano (2011)) has paid little attention to nonlinearities in the preferences for redistribution. Instead, the existing empirical evidence establishes linear associations that cannot identify the above nonlinear mechanisms of the preferences for redistribution. For example, Alesina and Angeletos (2005) argue that when there is a demand for fairness the complementarity between the optimal level of taxation and the equilibrium signal-tonoise ratio in the income distribution generates multiple equilibria. In the one equilibrium, taxes are higher, individuals invest and work less, and inequality is lower and as result the society desires high redistribution. In the other equilibrium, taxes are lower, individuals invest and work more, and inequality is higher and as result the society desires low redistribution. In general, all these theories imply threshold-type mechanisms in the sense that the preferences for redistribution may follow a different process depending whether the country is above or below that threshold value. In this paper we do three things. First, we extend the existing work on preferences for redistribution by allowing for multiple regimes using a generalized threshold regression model. Second, we focus argue that social norms may have subtle impact on the preferences for redistribution when they are modeled as endogenous social interactions. By social interactions we mean that the model will allow for interdependences among individuals in the preferences, beliefs, and constraints. Third, we explore various groups based on various socioeconomic distances at the regional or country level along the lines of Conley and Topa (2002). Using individual data from two complementary surveys the General Social Survey (GSS) and the World Values Survey (WVS) we employ threshold regression model to uncover the presence of multiple regimes in the preferences of redistribution. We find strong evidence that countries are organized into two regimes according to the degree of fairness, that is, the belief that hard work is more important in order to succeed in life. Countries with dominant beliefs that luck and connection is the main determinant for succeeding in life have higher preferences for redistribution. The marginal effect of fairness for this group of countries is positive as in Alesina and La Ferrara (2005). However, for countries with dominant beliefs that hard work is the main determinant for succeeding in life we obtain different results. While this set of countries has lower preferences for redistribution, the marginal effect of fairness is negative, indicating that individuals who believe that hard work is more important in order to succeed in life demand more redistribution. This finding is consistent with a modern version of Weber's hypothesis of a Protestant work ethic, combined with a charitable attitude towards the poor (Bjrnskov, Dreher, Fischer, Schnellenbach, and Gehringe (2013)) rather than Alesina and La Ferrara (2005). ABSTRACT FROM AUTHOR] Copyright of Proceedings: Ioannina Meeting on Applied Economics & Finance is the property of University of Ioannina, Department of Economics and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) 240 241 240-241

Barro and McCleary (2003, Religion and economic growth across countries. American Journal of Sociology 68: 760-781) is a key research contribution in the new literature exploring the macroeconomic effects of religious beliefs. This paper represents an effort to evaluate the strength of their claims. We evaluate their results in terms of replicability and robustness. Overall, their analysis generally meets the standard of statistical replicability, though not perfectly. On the other hand, we do not find that their results are robust to changes in their baseline statistical specification. When model-averaging methods are employed to integrate information across alternative statistical specifications, little evidence survives that religious variables help to predict cross-country income differences. © 2011 John Wiley & Sons, Ltd. 27 1059 1075 1059-1075

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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.

We introduce easy to implement regression-based methods for predicting quarterly real economic activity that use daily financial data and rely on forecast combinations of Mixed Data Sampling (MIDAS) regressions. We also extract a novel small set of daily financial factors from a large panel of about one thousand daily financial assets. Our analysis is designed to elucidate the value of daily information and provide real-time forecast updates of the current (nowcasting) and future quarters of real GDP growth. Our findings show that while on average the predictive ability of all models worsens substantially following the financial crisis that started in 2007, the models we propose suffer relatively less losses than the traditional ones. Moreover, these predictive gains are primarily driven by the classes of government securities, equities, and especially corporate risk.

We employ various local generalizations of the Solow growth model that model parameter heterogeneity using adult literacy rates and life expectancy at birth. The model takes the form of a semiparametric varying coefficient model along the lines of Hastie and Tibshirani (1993). The empirical results show substantial parameter heterogeneity in the cross-country growth process, a finding that is consistent with the presence of multiple steady-state equilibria and the emergence of convergence clubs. © 2011 by Emerald Group Publishing Limited. All rights reserved. 11 367 387 367-387

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. 30 1710 1719 1710-1719

This paper introduces the structural threshold regression (STR) model that allows for an endogenous 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, Econometrica 68, 575–603) and Caner and Hansen (2004, Econometric Theory 20, 813–843) to allow for the endogeneity of the threshold variable and regime-specific heteroskedasticity. Our estimation of the threshold parameter is based on a two-stage 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 confidence intervals. We also provide inference for the slope parameters based on a generalized method of moments. Finally, we investigate the performance of the asymptotic approximations using a Monte Carlo simulation, which shows the applicability of the method in finite samples.

We study regression models that involve data sampled at different frequencies. We derive the asymptotic properties of the NLS estimators of such regression models and compare them with the LS estimators of a traditional model that involves aggregating or equally weighting data to estimate a model at the same sampling frequency. In addition we propose new tests to examine the null hypothesis of equal weights in aggregating time series in a regression model. We explore the above theoretical aspects and verify them via an extensive Monte Carlo simulation study and an empirical application. © 2010 Elsevier B.V. All rights reserved. 158 246 261 246-261

There have been intensive debates on the role of aid in promoting economic development in developing countries by using cross-country analyses. Cross-country regression assuming linear relationship between aid and growth and without taking into heterogeneity of countries would produce biased estimates. To correct this, in this paper we investigate the relationship between foreign aid and growth using recently developed sample splitting methods that allow us to simultaneously uncover evidence for the existence of heterogeneity and nonlinearity. We also address 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 ethno-linguistic fractionalization. However, when we account for model uncertainty, we find no evidence to suggest that the relationship between aid and growth is nonlinear. In fact, our results suggest that the partial effect of aid on growth is likely to be weakly negative. In this sense, our findings suggest that aid is potentially counterproductive to growth with outcomes not meeting the expectations of donors. However due to the data comparability problem and inherent econometric problem in cross-country regression, more detailed country case studies are needed to evaluate the impact of aid at the country level and even project level. This can really answer the question that under what conditions what type of aid helped growth and poverty reduction in developing countries. The methodology developed in this paper can be used to identify typologies on other outcome variables, such as those included in the Millennium Development Goals.