Balázs Horváth

Monetary Transmission Mechanisms in Belarus

We explore monetary policy transmission by estimating VAR impulse response functions to illustrate the Belarusian economys response to unexpected changes in policy and exogenous variables. We find a significant exchange rate pass-through to prices, and interest rate policy following, rather than leading, financial market developments. Our estimated monetary policy reaction function shows the central bank striking a balance between real exchange rate stability and containing inflation. We discuss dollarization, administrative interventions, and other features complicating monetary policy transmission, review specific constraints and vulnerabilities, and conclude with observations on possible measures that could raise the effectiveness of monetary policy in Belarus.

The Role of Medium-Term Fiscal Frameworks for Transition Countries: The Case of Bulgaria

This paper discusses the foundations for a medium-term fiscal framework for Bulgaria, a transition economy aspiring to join the European Union. The paper argues that a well-designed framework can help to enhance the credibility of macroeconomic policies and facilitate preparations for EU membership. It presents an illustrative scenario for Bulgaria, utilizing a broad concept of net public debt.

Achieving Stabilization in Armenia

This paper examines the evolution, and impact on stabilization, of macroeconomic policies in Armenia during 1994-96. Fiscal and monetary policies have been effective in stabilizing the Armenian economy and facilitating significant growth, although they have not always worked in cohort. Seigniorage and the inflation tax declined dramatically as inflation fell, while dollarization was reversed but reached a plateau after mid-1995, affecting the demand for dram. The paper also presents quantitative indicators, which are suggestive of the trends discussed.

Summary, Directions for Future Research

The study has explored the econometric implications of the presence of an agent in the data generating mechanism who performs learning. It related the issues addressed to major areas in the literature. An illustrative model was presented in which even in the absence of any explicit dynamics the problem became nontrivial and dynamic by virtue of the presence of learning about the unknown parameter. The agent had to strike an optimal balance between current payoff maximization and generation of information in the future. The distinction between active and passive learning was made. On the basis of an argument on the curvature of the value function arising in the problem, active learning was shown to be generically optimal.

A Paradigmatic Example

The theoretical foundations for this class of models have been summarized in Easley and Kiefer (1988). A discrete time decision problem is considered where the decisionmaker chooses an action r in each period to maximize total expected discounted reward depending on the action chosen and the outcome, a random variable. The conditional distribution f(.|r, s) of the outcome given the action depends on an initially unknown parameter s. The decisionmaker begins with a prior belief about the unknown parameter and at the end of each period updates it via Bayes’ rule utilizing the latest observations on the action taken and the outcome. Easley and Kiefer take the additional simplifying step of integrating out the outcome and redefining the maximand to be the total expected discounted mean reward where the mean is calculated with respect to the conditional distribution f(.|r,s) and the belief distribution.

Tests for Exogeneity

Engle, Hendry and Richard (1983) and Hendry and Richard (1983) argue in a convincing manner that their notion of exogeneity is the natural one to use instead of classical (strict) exogeneity if the goal of the econometric ian is to use the simplest possible model without loss of relevant statistical information. Geweke (1984) on the other hand reveals the opposite side of the coin: while it is weak exogeneity that we are really after, that concept by itself cannot generate refutable hypotheses (see also Basmann (1965)). In other words, a model can always be constructed and parameters of interest can be chosen for which a designated set of variables is weakly exogenous — a simple way to do this is to specify the conditional model and the marginal model independently. Therefore weak exogeneity by itself does not supply enough restrictions that it can be subjected to statistical tests. So, in order to make weak exogeneity operational, concepts that generate empirically refutable hypotheses and which under reasonable assumptions are compatible with weak exogeneity are needed. And here is where we come a full circle: strict exogeneity is such a concept — though not the only one. Testing for strict exogeneity is possible (Sims (1972), Williams, Goodhart and Gowland (1976), Ciccolo (1978)), and such tests can be interpreted as joint tests of strict exogeneity and the assumptions that link weak exogeneity to strict exogeneity.