Efficiency Bounds for Estimating Linear Functionals of Nonparametric Regression Models with Endogenous Regressors

Consider a nonparametric regression model Y=mu*(X) + e, where the explanatory variables X are endogenous and e satisfies the conditional moment restriction E[e|W]=0 w.p.1 for instrumental variables W. It is well known that in these models the structural parameter mu* is 'ill-posed' in the sense that the function mapping the data to mu* is not continuous. In this paper, we derive the efficiency bounds for estimating linear functionals E[p(X)mu*(X)] and int_{supp(X)}p(x)mu*(x)dx, where p is a known weight function and supp(X) the support of X, without assuming mu* to be well-posed or even identified.

Does the Federal Reserve Follow a Non-Linear Taylor Rule?

The Taylor rule has become one of the most studied strategies for monetary policy. Yet, little is known whether the Federal Reserve follows a non-linear Taylor rule. This paper employs the smooth transition regression model and asks the question: does the Federal Reserve change its policy-rule according to the level of inflation and/or the output gap? I find that the Federal Reserve does follow a non-linear Taylor rule and, more importantly, that the Federal Reserve followed a non-linear Taylor rule during the golden era of monetary policy, 1985-2005, and a linear Taylor rule throughout the dark age of monetary policy, 1960-1979. Thus, good monetary policy is associated with a non-linear Taylor rule: once inflation approaches a certain threshold, the Federal Reserve adjusts its policy-rule and begins to respond more forcefully to inflation.

Technical Efficiency of State Owned Enterprises in China (1980-1989): An Assessment of the Economic Reforms

This paper uses Data Envelopment Analysis to examine changes in levels of technical efficiency over time in China's state-owned enterprises (SOEs) during 1980-1989. Our paper adds to the growing body of literature in this area by obtaining measures of technical efficiency of individual SOEs over years and by identifying how different aspects of the reforms have affected efficiency. We estimate a Tobit regression model, using the technical efficiency score as the dependent variable and a set of reform variables and firm attributes as regressors. We find that specific aspects of the reforms were very effective in improving technical efficiency.

An Appropriate Role for the Leadership: A Quantitative Analysis of the Effects of House Leadership on Open-Seat Races

This paper investigates the effects on open-seat races in the United States House of Representatives. This project focuses on the influence that the House leadership exerts on races. Generally, the leadership influences race through spending by party organizations and leadership visits. During each election cycle, national party organizations spend millions of dollars to get their candidates into office. I have developed a multiple regression model that measures different types of spending from the Democratic Congressional Campaign Committee, the National Republican Congressional Committee, and the Republican National Committee and the effects of these spending types on the election results. Also, the study examines the number of visits by each party’s leadership to each race. I introduced control variables that account for the year, the competitiveness of each race, and the individual candidate fundraising. In terms of statistical significance, the results were mixed showing one type of party spending to be highly influential in the outcome of the race. Competitiveness and individual candidate fundraising also achieved statistical significance. The study also includes a qualitative investigation of leadership visits and individual case studies in order to understand better the way in which the data interact in real campaigns.