Control variate method for stationary processes

The sample mean is one of the most natural estimators of the population mean based on independent identically distributed sample. However, if some control variate is available, it is known that the control variate method reduces the variance of the sample mean. The control variate method often assumes that the variable of interest and the control variable are i.i.d. Here we assume that these variables are stationary processes with spectral density matrices, i.e. dependent. Then we propose an estimator of the mean of the stationary process of interest by using control variate method based on nonparametric spectral estimator. It is shown that this estimator improves the sample mean in the sense of mean square error. Also this analysis is extended to the case when the mean dynamics is of the form of regression. Then we propose a control variate estimator for the regression coefficients which improves the least squares estimator (LSE). Numerical studies will be given to see how our estimator improves the LSE.     

OPTIMAL CONTRACTS FOR CENTRAL BANKERS AND PUBLIC DEBT POLICY*

We consider how the second‐best allocation corresponding to an optimal rule under the policy commitment of a central bank and a fiscal authority with a consolidated government budget constraint can be achieved, even though these authorities are unable to commit themselves to their optimal policies and ignore the strategic interaction between their policies. Our results show that the best practical institutional arrangement is to have an instrument‐independent central bank that controls the money supply to determine the rate of inflation and commits itself to an inflation target that depends on fiscal variables.     

A business cycle model with variable capacity utilization and demand disturbances

We develop a dynamic general-equilibrium model with demand (preference) shocks, estimated using Hall's (J. Labour Economics 15 (1997) 223) residual, that replicates U.S. business cycles well, at least compared to the real business cycle models. The key factor is cyclical capital utilization, which is based on imperfect competition, slow adjustments in capital stock, and fixed requirement of labor input. We also demonstrate theoretically that a representative-agent economy with preference shocks could be viewed as the reduced form of a heterogeneous-agents economy with incomplete markets. Specifically, a heterogeneous-agents economy with incomplete markets is aggregated into a representative-agent economy with preference shocks. This result would provide a microeconomic foundation for preference shock models. It is also shown that a shock to marginal utility of consumption and a shock to marginal disutility of labor have different effects.     

Business cycle turning points based on DEA-discriminant analysis

Recently, the turning points of business cycle are decided with wide viewpoints after passing a couple of years from the points. This study tries to develop a model for judging the turning points in real-time by using a non-parametric approach, DEA-discriminant analysis, because we have sometimes faced sudden changes of economy and non-parametric approaches are useful for covering these movements. The constructed model succeeds to separate periods in Japanese economic expanding and recession terms, and the model would be helpful for the real-time judgments of the turning points of business cycle.     

Unemployment and indeterminacy

Using an efficiency-wage model, we examine the relationship between indeterminacy and unemployment insurance. It is shown that the less unemployment insurance is, the more likely equilibrium is to be indeterminate. Equilibrium can be indeterminate even without externalities or increasing returns, which makes a sharp contrast to the recent literature on indeterminacy. Our result is based on the fact that the no-shirking condition with marginal utility of wealth kept constant is downward sloping when income insurance is not perfect.     

Statistical Inference Using Stochastic Switching Models for the Discrimination of Unobserved Display Promotion from POS Data

The execution of price and/or display promotion has a significant effect on the sales of a brand sold in a supermarket. Information on price and/or sales is available from POS data. However, unless an investigator collects information on the execution of display promotions from every retail store, such information is unavailable. This paper presents a method of identifying whether display promotion has been executed without having to visit individual stores. We treat the execution/non-execution of a display promotion as a state variable. An unknown stationary probability matrix is assumed to describe the probability of a transition between states. Each state is characterized by a different stationary time series model with unknown parameters. The objective of the analysis is to identify the model and to assign a probability model for each state at each time instant. Finally, we provide a high precision estimator of a past execution/non-execution of a display promotion based on the proposed model.     

Global liquidity trap

How should monetary policy respond to a “global liquidity trap,” where the two countries may fall into a liquidity trap simultaneously? Using a two-country New Open Economy Macroeconomics model, we first characterize optimal monetary policy, and show that the optimal rate of inflation in one country is affected by whether or not the other country is in a liquidity trap. We next examine how well the optimal monetary policy is approximated by relatively simple monetary policy rules. The interest-rate rule targeting the producer price index performs well in this respect.