This paper conducts quantile regressions and obtains detailed estimates of monetary policy rules in Japan using a sample that includes recent periods of zero interest rates. Taking into account censoring and endogeneity, we compute censored quantile instrumental variable estimators and compare them with estimates from uncensored quantile regressions. The estimation results indicate that not accounting for censoring of interest rates tends to result in downwardly biased estimates. Moreover, our censored quantile regressions lead to relatively flat coefficients of inflation and insignificant coefficients of the output gap over the conditional interest rate distribution, suggesting that monetary policy in Japan may be well described by a linear rule.Keywords Quantile regression · Censoring · Japan · Taylor rule · Zero lower bound JEL Classification C21 · C26 · E52 · E58 B Jau-er Chen
We propose an econometric procedure based mainly on the generalized random forests method. Not only does this process estimate the quantile treatment effect nonparametrically, but our procedure yields a measure of variable importance in terms of heterogeneity among control variables. We also apply the proposed procedure to reinvestigate the distributional effect of 401(k) participation on net financial assets, and the quantile earnings effect of participating in a job training program.
This paper examines nonparametric regression with an exogenous threshold variable, allowing for an unknown number of thresholds.Given the number of thresholds and corresponding threshold values, we first establish the asymptotic properties of the local constant estimator for a nonparametric regression with multiple thresholds. However, the number of thresholds and corresponding threshold values are typically unknown in practice. We then use our testing procedure to determine the unknown number of thresholds and derive the limiting distribution of the proposed test. The Monte Carlo simulation results indicate the adequacy of the modified test and accuracy of the sequential estimation of the threshold values. We apply our testing procedure to an empirical study of the 401(k) retirement savings plan with income thresholds.
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