When estimating higher-order derivatives of a partial differential equation, it is often essential to compute approximations for artificial boundaries. In this paper we formulate an explicit discretization model for approximation of beta-coefficient of Capital Asset Pricing Model (CAPM). The...

This paper tests the relationship between above market returns and beta, size, leverage, book-to-market equity and earning-price ratios for Bucharest Stock Exchange common stocks. Results from cross-sectional regressions document that both book-to-market equity and earning-price ratios are...

We study semiparametric two-step estimators which have the same structure as parametric doubly robust estimators in their second step, but retain a fully nonparametric specification in the first step. Such estimators exist in many economic applications, including a wide range of missing data and...

The literature contrasting structural and experimental econometrics highlights that stronger assumptions are required to identify direct effects than total effects. This paper examines the additional assumptions required to predict future experience using either type of causal effect identified...

This paper examines the ability of equity open interests from options markets to forecast underlying stock price for the maturity date and to examine if the forecast prices can be used as a guide to design trading rules. GMM estimation method is used on a set of widely held stocks from US...

This study follows and extends Sias (2004) to examine whether Qualified Foreign Institutional Investors' (QFIIs') herding behavior exists in the Taiwan stock market. By testing the cross-sectional dependence in QFII's demand over two adjacent months and decomposing them into QFIIs' own cascades...

This paper uses model-based recursive partitioning to study economic growth in the 255 European Union NUTS2 regions over the period 1995-2005. The starting point of the analysis is a human-capital augmented Solow-type growth equation similar in spirit to Mankiw, Romer, and Weil (1992). Initial...

Due to their well-known indeterminacies, factor models require identifying assumptions to guarantee unique parameter estimates. For Bayesian estimation, these identifying assumptions are usually implemented by imposing constraints on certain model parameters. This strategy, however, may result...

Measuring bias is important as it helps identify flaws in quantitative forecasting methods or judgmental forecasts. It can, therefore, potentially help improve forecasts. Despite this, bias tends to be under represented in the literature: many studies focus solely on measuring accuracy. Methods...

Nonparametric techniques are usually seen as a statistic device for data description and exploration, and not as a tool for estimating models with a richer economic structure, which are often required for policy analysis. This paper presents an example where nonparametric flexibility can be...