Price Increasing Competition? Experimental Evidence

Economic intuition suggests that increased competition generates lower prices. However, recent theoretical work shows that a monopolist may charge a lower price than a firm facing a competitor selling a differentiated product. The direction of the price change when competition is introduced is dependent upon the joint distribution of buyer values for the two products. We explore this relationship using controlled laboratory experiments. Our results indicate that the distribution of buyer values does affect prices in a manner consistent with the theoretical predictions, although price increasing competition is rare due in part to overly intense competition regardless of the distribution of buyer values. We also explore pricing dynamics and find that sellers are more sensitive to their rivals when buyer values are positively correlated.product differentiation, pricing, market structure, market experiments

A Semiparametric Time Trend Varying Coefficients Model: With An Application to Evaluate Credit Rationing in U.S. Credit Market

In this paper, we propose a new semiparametric varying coefficient model which extends the existing semi-parametric varying coefficient models to allow for a time trend regressor with smooth coefficient function. We propose to use the local linear method to estimate the coefficient functions and we provide the asymptotic theory to describe the asymptotic distribution of the local linear estimator. We present an application to evaluate credit rationing in the U.S. credit market. Using U.S. monthly data (1952.1-2008.1) and using inflation as the underlying state variable, we find that credit is not rationed for levels of inflation that are either very low or very high. For the remaining values of inflation in the sample, we find that credit is rationed and the Mundell-Tobin effect holds.non-stationarity, semi-parametric smooth coefficients, nonlinearity, credit rationing

Essays in Applied Macroeconomics: Asymmetric Price Adjustment, Exchange Rate and Treatment Effect

This dissertation consists of three essays. Chapter II examines the possible asymmetric response of gasoline prices to crude oil price changes using an error correction model with GARCH errors. Recent papers have looked at this issue. Some of these papers estimate a form of error correction model, but none of them accounts for autoregressive heteroskedasticity in estimation and testing for asymmetry and none of them takes the response of crude oil price into consideration. We find that time-varying volatility of gasoline price disturbances is an important feature of the data, and when we allow for asymmetric GARCH errors and investigate the system wide impulse response function, we find evidence of asymmetric adjustment to crude oil price changes in weekly retail gasoline prices Chapter III discusses the relationship between fiscal deficit and exchange rate. Economic theory predicts that fiscal deficits can significantly affect real exchange rate movements, but existing empirical evidence reports only a weak impact of fiscal deficits on exchange rates. Based on US dollar-based real exchange rates in G5 countries and a flexible varying coefficient model, we show that the previously documented weak relationship between fiscal deficits and exchange rates may be the result of additive specifications, and that the relationship is stronger if we allow fiscal deficits to impact real exchange rates non-additively as well as nonlinearly. We find that the speed of exchange rate adjustment toward equilibrium depends on the state of the fiscal deficit; a fiscal contraction in the US can lead to less persistence in the deviation of exchange rates from fundamentals, and faster mean reversion to the equilibrium. Chapter IV proposes a kernel method to deal with the nonparametric regression model with only discrete covariates as regressors. This new approach is based on recently developed least squares cross-validation kernel smoothing method. It can not only automatically smooth the irrelevant variables out of the nonparametric regression model, but also avoid the problem of loss of efficiency related to the traditional nonparametric frequency-based method and the problem of misspecification based on parametric model

Some Recent Developments on Nonparametric Econometrics

In this paper, we survey some recent developments of nonparametric econometrics in the following areas: (i) nonparametric estimation of regression models with mixed discrete and continuous data; (ii) nonparametric models with nonstationary data; (iii) nonparametric models with instrumental variables; and (iv) nonparametric estimation of conditional quantile functions. In each of the above areas, we also point out some open research problems.This paper was publised in Advances in Econometrics, Volume 25 (2009), 495–549

Price Increasing Competition? Experimental Evidence

Economic intuition suggests that increased competition generates lower prices. However, recent theoretical work shows that a monopolist may charge a lower price than a firm facing a competitor selling a differentiated product. The direction of the price change when competition is introduced is dependent upon the joint distribution of buyer values for the two products. We explore this relationship using controlled laboratory experiments. Our results indicate that the distribution of buyer values does affect prices in a manner consistent with the theoretical predictions, although price increasing competition is rare due in part to overly intense competition regardless of the distribution of buyer values. We also explore pricing dynamics and find that sellers are more sensitive to their rivals when buyer values are positively correlated

Working from a distance: Productivity dispersion and labor reallocation

Following the shocks of the COVID-19 pandemic, the economy may be significantly changed relative to the pre-pandemic world. One critical shift induced by the COVID- 19 pandemic is a need for physical distance (at least 6 feet apart) between workers and customers. In this study, we examine the impacts of social distancing in the workplace on employment and productivity across industries. Using our constructed measure of adaptability to social distancing, we empirically find that industries that are more adaptive to social distancing had less decline in employment and productivity during the pandemic. Using this empirical evidence, our model predicts that employment and productivity dispersion would induce labor reallocation across sectors, while imperfect labor mobility may result in a long road to economic recovery

Working from a Distance : Productivity Dispersion and Labor Reallocation

Following the shocks of the COVID-19 pandemic, the economy may be significantly changed relative to the pre-pandemic world. One critical shift induced by the COVID19 pandemic is a need for physical distance (at least 6 feet apart) between workers and customers. In this study, we examine the impacts of social distancing in the workplace on employment and productivity across industries. Using our constructed measure of adaptability to social distancing, we empirically find that industries that are more adaptive to social distancing had less decline in employment and productivity during the pandemic. Using this empirical evidence, our model predicts that employment and productivity dispersion would induce labor reallocation across sectors, while imperfect labor mobility may result in a long road to economic recovery

A Semiparametric Time Trend Varying Coefficients Model: With An Application to Evaluate Credit Rationing in U.S. Credit Market

In this paper, we propose a new semiparametric varying coefficient model which extends the existing semi-parametric varying coefficient models to allow for a time trend regressor with smooth coefficient function. We propose to use the local linear method to estimate the coefficient functions and we provide the asymptotic theory to describe the asymptotic distribution of the local linear estimator. We present an application to evaluate credit rationing in the U.S. credit market. Using U.S. monthly data (1952.1-2008.1) and using inflation as the underlying state variable, we find that credit is not rationed for levels of inflation that are either very low or very high; and for the remaining values of inflation, we find that credit is rationed and the Mundell-Tobin effect holds.non-stationarity, semi-parametric smooth coefficients, nonlinearity, credit rationing