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

This dissertation consists of three essays. Chapter II examines the possibleasymmetric response of gasoline prices to crude oil price changes using an errorcorrection model with GARCH errors. Recent papers have looked at this issue. Some ofthese papers estimate a form of error correction model, but none of them accounts forautoregressive heteroskedasticity in estimation and testing for asymmetry and none ofthem takes the response of crude oil price into consideration. We find that time-varyingvolatility of gasoline price disturbances is an important feature of the data, and when weallow for asymmetric GARCH errors and investigate the system wide impulse responsefunction, we find evidence of asymmetric adjustment to crude oil price changes inweekly retail gasoline pricesChapter III discusses the relationship between fiscal deficit and exchange rate.Economic theory predicts that fiscal deficits can significantly affect real exchange ratemovements, but existing empirical evidence reports only a weak impact of fiscal deficitson exchange rates. Based on US dollar-based real exchange rates in G5 countries and aflexible varying coefficient model, we show that the previously documented weak relationship between fiscal deficits and exchange rates may be the result of additivespecifications, and that the relationship is stronger if we allow fiscal deficits to impactreal exchange rates non-additively as well as nonlinearly. We find that the speed ofexchange rate adjustment toward equilibrium depends on the state of the fiscal deficit; afiscal contraction in the US can lead to less persistence in the deviation of exchange ratesfrom fundamentals, and faster mean reversion to the equilibrium.Chapter IV proposes a kernel method to deal with the nonparametric regressionmodel with only discrete covariates as regressors. This new approach is based onrecently developed least squares cross-validation kernel smoothing method. It can notonly automatically smooth the irrelevant variables out of the nonparametric regressionmodel, but also avoid the problem of loss of efficiency related to the traditionalnonparametric frequency-based method and the problem of misspecification based onparametric model.