Robust misspecification tests for the Heckman’s two-step estimator

We construct and evaluate LM and Neyman’s C(α) tests based on bivariate Edgeworth expansions for the consistency of the Heckman’s two-step estimator in selection models, that is, for the marginal normality and linearity of the conditional expectation of the error terms. The proposed tests are robust to local misspecification in nuisance distributional parameters. Monte Carlo results show that instead of testing bivariate normality, testing marginal normality and linearity of the conditional expectations separately have a better size performance. Moreover, the robust variants of the tests have better size and similar power to non-robust tests, which determines that these tests can be successfully applied to detect specific departures from the null model of bivariate normality. We apply the tests procedures to women’s labor supply data

Nonparametric estimation of ATE and QTE: an application of Fractile Graphical Analysis

Nonparametric estimators for average and quantile treatment effects are constructed using Fractile Graphical Analysis, under the identifying assumption that selection to treatment is based on observable characteristics. The proposed method has two-steps: first, the propensity score is estimated, and second, a blocking estimation procedure using this estimate is used to compute treatment effects. In both cases, the estimators are proved to be consistent. Monte Carlo results show a better performance than other procedures based on the propensity score. Finally, these estimators are applied to a job training dataset

Informal Jobs and Trade Liberalisation in Argentina

Rapid trade liberalisation can exert profound effects on labour markets. Domestic firms, to sustain competitiveness for survival, could react through cutting labour benefits to achieve cost reductions. Alternatively, trade liberalisation may alter the industry composition of firms changing the aggregate formality rates. This paper studies the relationship between trade liberalisation and informality in Argentina. Using manufacturing industry-level data for 1992-2003, the results confirm the hypothesis that trade increases informality in industries that experience sudden foreign competition. This explains about a third of the increase in informality. Sectors with higher investment ratios are able to neutralize and reverse this effect

Instrumental variables quantile regression for panel data with measurement errors

This paper develops an instrumental variables estimator for quantile regression in panel data with fixed effects. Asymptotic properties of the instrumental variables estimator are studied for large N and T when Na/T ! 0, for some a > 0. Wald and Kolmogorov-Smirnov type tests for general linear restrictions are developed. The estimator is applied to the problem of measurement errors in variables, which induces endogeneity and as a result bias in the model. We derive an approximation to the bias in the quantile regression fixed effects estimator in the presence of measurement error and show its connection to similar effects in standard least squares models. Monte Carlo simulations are conducted to evaluate the finite sample properties of the estimator in terms of bias and root mean squared error. Finally, the methods are applied to a model of firm investment. The results show interesting heterogeneity in the Tobin’s q and cash flow sensitivities of investment. In both cases, the sensitivities are monotonically increasing along the quantiles

Argentina's default and the lack of dire consequences

We analyze the 2001 Argentine default on its foreign debt and its consequences in terms of the existing literature on sovereign debt default. It is our purpose to evaluate this experience and to see to what extent the Argentine case requires a re-thinking on the nature and consequences of defaults. We show that the Argentine case contradicts many of their standard predictions, in particular its posterior lack of access to international credit, restriction to international trade and negative economic growth. Moreover, it corroborates the historical fact that many defaulters “get away with it.

Can Poor Countries Lobby for More US Bilateral Aid?

This article explores if countries can lobby the US government for the allocation of US bilateral foreign aid. We consider an informational lobby model where lobbying has two effects. First, a direct effect by informing US policymakers about their countries' needs. Second, an indirect effect on policymakers by informing them about common interests in economic or geopolitical terms. The lobbyist thus influences the decisions about the allocation of aid resources. We estimate the effect of the recipient country's lobbying agents in obtaining foreign aid. The econometric results show that lobbying positively affects the amount of bilateral aid received

An equicorrelation Moulton factor in the presence of arbitrary intra-cluster correlation

This note highlights the potential pitfalls of using an equicorrelation model to estimate standard errors when the true model has arbitrary intra-cluster correlation. It derives a generalized equicorrelation Moulton factor that quantifies the potential biases in standard errors for OLS estimators. As with the famous Moulton factor, the key role is not played by the correlation of the error terms but rather by the intra-correlation of the covariates themselves

Earnings and Social Background: An evaluation of caste/ethnic wage differentials in the Nepalese labor market

This paper examines the sources of wage differentials among caste/ethnic groups, employing national survey data from Nepal. Our study shows that, in countries such as Nepal which have imperfect labour markets, the conventional Oaxaca decomposition methodology fails to estimate precisely the source of wage differential. Using an extended model, occupational choice, firm size distribution and the interaction between these two are employed along with the conventionally used measures of human capital endowments of different groups, to estimate these effects. Our results indicate that the lack of access to better paying occupations and larger firms, rather than differences in human capital, are the main factors underlying the caste/ethnic wage differentia in Nepal. Furthermore, empirical evidence is not found in favour of government policy of "affirmative action" to contribute yet in narrowing down the caste/ethnic wage differential in the labour market

Threshold quantile autoregressive models

We study in this article threshold quantile autoregressive processes. In particular we propose estimation and inference of the parameters in nonlinear quantile processes when the threshold parameter defining nonlinearities is known for each quantile, and also when the parameter vector is estimated consistently. We derive the asymptotic properties of the nonlinear threshold quantile autoregressive estimator. In addition, we develop hypothesis tests for detecting threshold nonlinearities in the quantile process when the threshold parameter vector is not identified under the null hypothesis. In this case we propose to approximate the asymptotic distribution of the composite test using a p-value transformation. This test contributes to the literature on nonlinearity tests by extending Hansen’s (Econometrica 64, 1996, pp.413-430) methodology for the conditional mean process to the entire quantile process. We apply the proposed methodology to model the dynamics of US unemployment growth after the Second World War. The results show evidence of important heterogeneity associated with unemployment, and strong asymmetric persistence on unemployment growth

Quantile autoregressive distributed lag model with an application to house price returns

This paper studies quantile regression in an autoregressive dynamic framework with exogenous stationary covariates. Hence, we develop a quantile autoregressive distributed lag model (QADL). We show that these estimators are consistent and asymptotically normal. Inference based on Wald and Kolmogorov-Smirnov tests for general linear restrictions is proposed. An extensive Monte Carlo simulation is conducted to evaluate the properties of the estimators. We demonstrate the potential of the QADL model with an application to house price returns in the United Kingdom. The results show that house price returns present a heterogeneous autoregressive behavior across the quantiles. The real GDP growth and interest rates also have an asymmetric impact on house prices variations