Applied Econometric Time Series

It is well known that a linear model may forecast better than a nonlinear one, even when the nonlinear model is consistent with the actual data-generating process. We propose a simple pretest to help determine whether it is worthwhile to forecast a series using a STAR model. In particular, we extend Teräsvirta’s in-sample test for LSTAR and ESTAR behavior to multistep-ahead out-of-sample forecasts. We illustrate the pretest using real exchange rates of various OECD countries.

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We estimate a number of macroeconomic variables as logistic smooth transition autoregressive(LSTAR) processes with uncertainty as the transition variable. For a number of important macroeconomic variables, we show (i) a positive shock to uncertainty has a greater effect than a negative shock, and (ii) the effect of the uncertainty shock is highly dependent onthe state of the economy. Hence, the usual linear estimates concerning the consequences ofuncertainty are underestimated in circumstances such as the recent financial crisis.

Data Code(Figs 1 to 4) Code(Figs 6,7,8) Code(Section 5.2 and Fig 5) 

Code(Table 1)  Code(Tables 2 and 3)

We show that the Taylor rule should be formulated as a threshold process such that the Federal Reserve acts more aggressivelyvin some circumstances than in others. Specifically, we find that a modified threshold modelthat is consistent with “opportunistic” monetary policy.

DATA  CODE  THRESHTEST.SRC  BIC.SRC

LINK

Taylor (1979) shows that there is a permanent tradeoff between the volatility of the output gapand the volatility of inflation. However, Friedman (2006) points out that it is more likely to serve as an efficiency locusthat can be used to gauge the appropriateness of monetary policy. Using data from 1875 onward,we examine the efficiency of U.S. monetary policy by measuring the orthogonal distancebetween the observed volatilities of the output gap and inflation from the Taylor curve.

APPENDIX  DATA   Code

We trace the timing of the so-called “Great Moderation” across many subsectors of the economy. We find that the interest rate sensitive sectors generally experience a much earlier volatility decline than other large sectors of the economy. The changes in Federal Reserve stabilization policies that occurred during the early 1980s support the view that improved monetary policy played an important role in stabilizing real economic activity.

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This article develops critical values to test the null hypothesis of a unit root against the alternative of stationarity with asymmetric adjustment. Specific attention is paid to threshold and momentum threshold autoregressive processes. The use of the tests is illustrated using the term structure of interest rates. Also see the first Programming Manual for more details.

DATA  RATS Procedure  Code    Additional Critical Values

Generalizes the Enders-Granger test to allow for threshold cointegration.

RATS Procedure