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This paper analyses the relationship between production subsidies and firms' export performance using a very comprehensive and recent firm-level database and controlling for the endogeneity of subsidies. It documents robust evidence that production subsidies stimulate export activity at the intensive margin, although this effect is conditional on firm characteristics. In particular, the positive relationship between subsidies and the intensive margin of exports is strongest among profit-making firms, firms in capital-intensive industries, and those located in non-coastal regions. Compared to firm characteristics, the extent of heterogeneity across ownership structure (SOEs, collectives, and privately owned firms) proves to be relatively less important.

PurposeThe authors investigated cocoa farmers' access to subsidized fertilizer in Ghana and implications on productivity.Design/methodology/approachPrimary data were sourced from 435 cocoa farmers. Cragg hurdle and two-step Tobit model with continuous endogenous regressors/covariates were applied for the drivers of cocoa farmers' participation in fertilizer subsidy programme and productivity. Propensity score matching (PSM), inverse-probability weights (IPW) and augmented inverse-probability weights (AIPW) were applied for productivity impact assessment of fertilizer subsidy.FindingsAll the farmers were aware of fertilizer subsidy for cocoa production in Ghana. Farmers became aware of fertilizer subsidy through extension officers, media and other farmers. Half of cocoa farmers benefitted from fertilizer subsidy. Averagely, cocoa farmers purchased 292 kg of subsidized fertilizer. Many socio-economic, farm-level characteristics and institutional factors determine cocoa farmers' participation in fertilizer subsidy programme, quantity of subsidized fertilizer obtained and productivity. Beneficiaries of fertilizer subsidy recorded higher cocoa productivity than non-beneficiaries. Hence, fertilizer subsidy for cocoa production in Ghana leads to a gain in productivity.Practical implicationsThere should be more investments in fertilizer subsidy so that all cocoa farmers benefit and obtain the required quantities.Originality/valueThe authors provide new evidence on cocoa productivity gain or loss emanating from fertilizer subsidy by combining different impact assessment techniques for deeper analysis: PSM, IPW and AIPW.

I study a simple, widely applicable approach to handling the initial conditions problem in dynamic, nonlinear unobserved effects models. Rather than attempting to obtain the joint distribution of all outcomes of the endogenous variables, I propose finding the distribution conditional on the initial value (and the observed history of strictly exogenous explanatory variables). The approach is flexible, and results in simple estimation strategies for at least three leading dynamic, nonlinear models: probit, Tobit and Poisson regression. I treat the general problem of estimating average partial effects, and show that simple estimators exist for important special cases.

We present a simple way to estimate the effects of changes in a vector of observable variables X on a limited dependent variable Y when Y is a general nonseparable function of X and unobservables, and X is independent of the unobservables. We treat models in which Y is censored from above, below, or both. The basic idea is to first estimate the derivative of the conditional mean of Y given X at x with respect to x on the uncensored sample without correcting for the effect of x on the censored population. We then correct the derivative for the effects of the selection bias. We discuss nonparametric and semiparametric estimators for the derivative. We also discuss the cases of discrete regressors and of endogenous regressors in both cross section and panel data contexts.

The greater market orientation of European dairy production, caused by the end of quota regime, is likely to have consequences on less favoured areas, where breeding of dairy cattle plays both a crucial socio-economic and environmental role. Within this new framework, endogenous factors determining spatial reorganisation of the sector are becoming of increasing relevance. Based on these considerations, this study analyses the impact of the three broader classes of location determinants suggested by economic theory - factor endowment, market potential, and spatial agglomeration externalities - on the spatial pattern of milk production in Molise, a rural region in the south of Italy. Milk production is measured in term of dairy cows per hectare. The truncated distribution of this variable and its high degree of spatial autocorrelation prompted us to apply a Spatial Autoregressive Tobit model. Estimation results reveal that all three categories have a positive effect on the location of milk production, even if the influence of factor endowment (intended as forage area), and market potential (measured in term of proximity of dairy companies) is quite limited. On the contrary, the impact of spatial externalities (related variety) on the regional localisation of milk production is strongly significant. These results cast some doubts on the current measures of intervention and might suggest a new policy framework both at firm and spatial level

This paper explores the impact of residential density on households' vehicle type and usage choices using the 2001 National Household Travel Survey (NHTS). Attempts to quantify the effect of urban form on households' vehicle choice and utilization often encounter the problem of sample selectivity. Household characteristics that are unobservable to the researchers might determine simultaneously where to live, what vehicles to choose, and how much to drive them. Unless this simultaneity is modeled, any relationship between residential density and vehicle choice may be biased. This paper extends the Bayesian multivariate ordered probit and tobit model developed in Fang (2008) to treat local residential density as endogenous. The model includes equations for vehicle ownership and usage in terms of number of cars, number of trucks (vans, sports utility vehicles, and pickup trucks), miles traveled by cars, and miles traveled by trucks. We carry out policy simulations that show that an increase in residential density has a negligible effect on car choice and utilization, but slightly reduces truck choice and utilization. The largest impact we find is a -.4 arc elasticity of truck fuel use with respect to density. We also perform an out-of-sample forecast using a holdout sample to test the robustness of the model.

We give semiparametric identification and estimation results for econometric models with a regressor that is endogenous, bound censored, and selected; it is called a Tobin regressor. First, we show that the true parameter value is set‐identified and characterize the identification sets. Second, we propose novel estimation and inference methods for this true value. These estimation and inference methods are of independent interest and apply to any problem possessing the sensitivity structure, where the true parameter value is point‐identified conditional on some nuisance parameter values that are set‐identified. By fixing the nuisance parameter value in some suitable region, we can proceed with regular point and interval estimation. Then we take the union over nuisance parameter values of the point and interval estimates to form the final set estimates and confidence set estimates. The initial point or interval estimates can be frequentist or Bayesian. The final set estimates are set‐consistent for the true parameter value, and confidence set estimates have frequentist validity in the sense of covering this value with at least a prespecified probability in large samples. Our procedure may be viewed as a formalization of the sensitivity analysis in the sense of Leamer (1985). We apply our identification, estimation, and inference procedures to study the effects of changes in housing wealth on household consumption. Our set estimates fall in plausible ranges, significantly above low ordinary least squares estimates and below high instrumental variables estimates that do not account for the Tobin regressor structure.

In this paper a count data regression model accounting for endogenous censoring with household specific censoring thresholds is presented. The presented modelling approach is utilized in an analysis of household choice of total number of nights to spend on monthly recreational trips. The empirical study reveals that the suggested approach is feasible and that accounting for endogenous censoring gives a better fit to the data.

The errors-in-variables (EIV) problem is pervasive in econometrics but has not received the attention it deserves, perhaps because it is difficult to resolve. The first objective of this paper is to demonstrate the effectiveness of recently developed methods to deal with the EIV problem in models with censoring. The second objective of this paper is to empirically examine, in light of the EIV problem, theories of endogenous protection that have become important in trade theory in their ability to explain why nations do not follow the traditional economic maxim of free trade. These theories emphasizing political-economic factors have gained momentum based on a set of empirical studies that have sought to prove their validity. Whether inferences about the theories of endogenous protection are gravely affected by errors in variables is examined using data on U. S. nontariff barriers with respect to nine developed countries. The theoretical developments in Klepper (1988) and Klepper and Leamer (1984) are combined with a result from Levine (1986), which usefully extends the use of EIV diagnostics to a model with censoring.

A simple consistent estimator of a simultaneous-equation Tobit model are analyzed. In a 2-equation model of this nature, one endogenous variable is completely observed and the other truncated. The results of the model indicate that the asymptotic variance, covariance matrices are straightforward and their complexity is not essential. The principles on which the proposed estimators are based can be applied to other situations where structural parameters need to be determined from the estimates of reduced-form parameters.