We present an algorithm and software routines for computing nth-order approximate solutions to dynamic, discrete-time rational expectations models around a nonstochastic steady state. We apply these routines to investigate the optimal monetary policy with commitment (and from a ``timeless...

The main goal of this paper is to investigate the role of campaign fund in congressional careers. To achieve this goal, we specify a dynamic model of career decisions of a member of Congress. In particular, we model how the amount of campaign funds raised affects the probability of winning...

Price caps are a popular form of monopoly price regulation. One of its disadvantages is the perverse incentives that regulated firms might have to scamp on cost reducing effort during the last years before a price review. In order to avoid this problem a “rolling cap†contract was...

The recently proposed family of hypernormal density functions possess the analytically convenient and computationally efficient property of closed form moments and anti-derivatives in the univariate case. While this result allows many univariate applications to be solved faster and/or more...

It is now widely understood how to obtain first-order accurate approximations to the solution to a dynamic, stochastic general equilibrium model (DSGE model). Such solutions are fairly easy to construct and useful for a wide variety of purposes. They are likely to be accurate enough to be a...

In times of low-inflation, conventional monetary policy is perpetually exposed to the risk of being caught by the liquidity trap. As a part of a pre-emptive monetary policy to avoid the liquidity trap, many economists have pointed out that this risk can be possibly circumvented by targeting a...

Understanding and forecasting financial time series depend crucially on identifying any non-linearity which may be present. Recent developments in tests for non-linearity very commonly display low power, most likely because of over-smoothing and discarding pertinent information. In this...

This paper extends the linear lasso estimators to non-linear case. We are especially interested in GMM type of Lasso estimators. Lasso estimators are generalization of ridge regression in least squares. With this setup we can deal with identification problem introduced by weak instruments. When...

The use of the Beveridge Nelson decomposition in macroeconomic analysis involves the truncation and estimation of infinite weighted sums of random variables, whereas the single source of error (SSE) state space approach provides a simple and effective framework that leads to exactly the same...