This paper considers measures of uncertainty used in economic estimation. Our first contribution is to address the theoretical relationship between cross-section and time series measures, highlighting the reasons why these might diverge. In a subsequent empirical section, we compare measures of...

This paper investigates the effect of exchange rate volatility on US-UK bilateral trade flows. As part of econometric problems arising from a generated variable, we consider a special case when an ARCH type auxiliary model is used to measure uncertainty in the exchange rate and discuss a...

This paper investigates the effect of exchange rate volatility on US-UK bilateral trade flows. As part of econometric problems arising from a generated variable, we consider a special case when an ARCH type auxiliary model is used to measure uncertainty in the exchange rate and discuss a...

Foreign Direct Investment has become an important source of long-term capital inflows for less developed countries in the last two decades. As documented in previous literature, FDI flows may increase permanently domestic output and represent an important source of technological spillovers for...

We use a novel data set and identification strategy to empirically detect the presence and magnitude of local social interactions effects in the labor market. We argue that the use of informal referrals has implications for the spatial distribution of residential and work locations, that can...

This paper is concerned with estimating the additive components of a nonparametric additive quantile regression model. We develop an estimator that is asymptotically normally distributed with a rate of convergence in probability of $n^{-r/(2r+1)}$ when the additive components are $r$-times...

In this paper, we are interested in a stochastic frontier model in which observable characteristics of the firms affect their levels of technical inefficiency. Let u ≥ 0 be the one-sided error reflecting technical inefficiency, and let z be a set of variables that affect u. We write u as...

This paper proposes shrinkage methods in instrumental variable estimations to solve the ``many instruments'' problem. Even though using a large number of instruments reduces the asymptotic variances of the estimators, it has been observed both in theoretical works and in practice that in finite...

Quantile regression (QR) methods fit a linear model for conditional quantiles, just as ordinary least squares (OLS) regression estimates a linear model for conditional means. An attractive feature of the OLS estimator is that it gives a minimum mean square error approximation to the conditional...