The study evaluates the efficiency of government intervention using a vertical structured model including imperfectly competitive agricultural input markets, the bread grain market, and the imperfectly competitive food industry. To test for policy efficiency the actually observed bread grain...

When deciding on the social desirability of public investment, the cost of a project is sometimes adjusted by a factor known as the Marginal Cost of Public Funds (MCP F ), which captures the cost of raising public funds through distortionary taxation. However, there is no scholarly consensus on...

Almost all theoretical work on how to calculate the marginal deadweight loss has been done for linear taxes and for variations in linear budget constraints. This is quite surprising since most income tax systems are nonlinear, generating nonlinear budget constraints. Instead of developing the...

Among the wide variety of policy options adopted worldwide to control carbon emissions, one of the most environmentally effective and economically efficient is represented by carbon tax, that aims to recoup the damage arising from polluting production processes. In this paper, we focus on the...

This chapter discusses identification of common selection models of the labor market. We start with the classic Roy model and show how it can be identified with exclusion restrictions. We then extend the argument to the generalized Roy model, treatment effect models, duration models, search...

In economics it is common to distinguish between different time horizons (i.e. short run, medium run, and long run). Engle (1974) proposed combining the discrete Fourier transform with a band spectrum regression to estimate models that separates between different time horizons. In this paper we...

We develop non-parametric instrumental variable estimation and inferential theory for econometric models with possibly endogenous regressors whose coefficients can vary over time either deterministically or stochastically, and the time-varying and uniform versions of the standard Hausman...

We introduce a Bayesian approach to predictive density calibration and combination that accounts for parameter uncertainty and model set incompleteness through the use of random calibration functionals and random combination weights. Building on the work of Ranjan and Gneiting (2010) and...

We propose a simple class of semiparametric multivariate GARCH models, allowing for asymmetric volatilities and time-varying conditional correlations. Estimates for time-varying conditional correlations are constructed by means of a convex combination of estimates for averaged correlations...

We provide a convenient econometric framework for the analysis of nonlinear dependence in financial applications. We introduce models with constrained nonparametric dependence, which specify the conditional distribution or the copula in terms of a one-dimensional functional parameter. Our...