the objective of this study is to estimate the demand for money in iran using the autoregressive distributed lag (ardl) approach to cointegration analysis. the empirical results show that there is a unique cointegrated and stable long-run relationship among m1 monetary aggregate, income, inflation and exchange rate. we find that the income elasticity and exchange rate coefficients are positive ...

Within a flexible regression model (Hamilton, 2001) we offer a battery of new Lagrange multiplier statistics that circumvent the problem of unidentified nuisance parameters under the null hypothesis of linearity and that are robust to the specification of the covariance function that defines the random field. These advantages are the result of (i) switching from the L2 to the L1 norm; and (ii) ...

The traditional M test requires a consistent estimation of the asymptotic variancecovariance matrix of the estimated moments (the AVC matrix). By extending the approach of Kiefer, Vogelsang, and Bunzel (KVB; 2000, Econometrica), Kuan and Lee (KL; 2006, Journal of the American Statistical Association) contributed a new type of M test without the AVC matrix estimation but with recursive model est...

A new test for hysteresis based on a nonlinear unobserved components model is proposed. Observed unemployment rates are decomposed into a natural rate component and a cyclical component. Threshold type nonlinearities are introduced by allowing past cyclical unemployment to have a different impact on the natural rate depending on the regime of the economy. The impact of lagged cyclical shocks on...

In nonparametric tests for serial independence the marginal distribution of the data acts as an infinite dimensional nuisance parameter. The decomposition of joint distributions in terms of a copula density and marginal densities shows that in general empirical marginals carry no information on dependence. It follows that the order of ranks is sufficient for inference, which motivates transform...

This paper develops a new framework and statistical tools to analyze stock returns using high frequency data. We consider a continuous-time multi-factor model via a continuous-time multivariate regression incorporating realistic empirical features, such as persistent stochastic volatilities with leverage effects. We find that conventional regression approach often leads to misleading and incons...

There are a large number of tests for instability or breaks in coefficients in regression models designed for different possible departures from the stable model. We make two contributions to this literature. First, we consider a large class of persistent breaking processes that lead to asymptotically equivalent efficient tests. Our class allows for many or relatively few breaks, clustered brea...

Numerous authors have suggested that the price-earnings (P/E) ratio can be used to predict the future movement of stock prices. Such arguments are based on the belief that P/E ratios are mean-reverting. But are the S&P P/E ratios really mean reverting? A review of the literature finds arguments on both sides, but the issue of mean reversion has not been tested adequately. Using unit roots and m...

We develop a specification test of predictive densities based on that the generalized residuals of correctly specified predictive density models are i.i.d. uniform. The proposed sequential test examines the hypotheses of serial independence and uniformity in two stages, wherein the first stage test of serial independence is robust to violation of uniformity. The approach of data driven smooth t...