Econometric models—representations of major cause-and-effect relationships in an economy—are a relatively new aid to policymakers. The author shows how they may be constructed and used and indicates some of their limitations.
We examine the effects of aid on growth-- in cross-sectional and panel data--after correcting for the bias that aid typically goes to poorer countries, or to countries after poor performance. Even after this correction, we find little robust evidence of a positive (or negative) relationship between aid inflows into a country and its economic growth. We also find no evidence that aid works better in better policy or geographical environments, or that certain forms of aid work better than others. Our findings, which relate to the past, do not imply that aid cannot be beneficial in the future. But they do suggest that for aid to be effective in the future, the aid apparatus will have to be rethought. Our findings raise the question: what aspects of aid offset what ought to be the indisputable growth enhancing effects of resource transfers? Thus, our findings support efforts under way at national and international levels to understand and improve aid effectiveness.
This paper aims to measure the risk premium on French equities during 1960-92 and to evaluate how well theoretical models based on various representations of agents' preferences can explain it. Aside from the standard, time-additive utility function with constant relative risk aversion, three other utility functions are reviewed: a recursive utility function, a habit formation utility function, and a utility function that accounts for the interdependence of preferences. Both calibration and econometric estimations show that none of the studied marginal changes in the representation of agents' preferences are sufficient to solve both the equity premium puzzle and the risk-free rate puzzle.
Emerging markets are more volatile and face different types of shocks, in size and nature, compared to their developed counterparts. Accurate identification of the stochastic properties of shocks is difficult. We show evidence suggesting that uncertainty about the underlying stochastic process is present in commodity prices. In addition, we build a dynamic stochastic general equilibrium model with informational frictions, which explicitly considers uncertainty about the nature of shocks. When formulating expectations, the economy assigns some probability to the shocks being temporary even if they are actually permanent. Parameter instability in the stochastic process implies that optimal saving levels (debt holdings) should be higher (lower) compared to a process with fixed parameters. Imperfect information about the nature of shocks matters when commodity GDP shares are high. Thus, economic policies based on misperception of the underlying regime can lead to substantial over/under saving with important associated costs.
The relationship of stock returns and trading volume is the focus of much recent interest. I examine an economic model of a rational trader who operates in a market with transactions costs and noise trading. The level of trading affects the rational trader’s marginal cost of transacting; as a result, trading volume is a source of risk. This engenders an equilibrium relationship between returns and volume. The model also provides a simple way to scrutinize this relationship empirically. Empirical evidence supports the implications of the model.
This paper analyzes the dynamic interactions between the precision of information, technological development, and welfare within an overlapping generations model. More precise information about idiosyncratic production shocks has ambiguous effects on technological progress and welfare, which depend critically on the risk sharing capacity of the economy's financial system. For example, we show that with efficient risk sharing more precise information adversely affects the equilibrium risk allocation and creates a negative uncertainty-related welfare effect, at the same time as it accelerates technological progress and increases R&D investment.
Vicente Tuesta, Juan F. Rubio-Ramirez, and Mr. Pau Rabanal
A puzzle in international macroeconomics is that observed real exchange rates are highly volatile. Standard international real business cycle (IRBC) models cannot reproduce this fact. We show that TFP processes for the U.S. and the "rest of the world," is characterized by a vector error correction (VECM) and that adding cointegrated technology shocks to the standard IRBC model helps explaining the observed high real exchange rate volatility. Also we show that the observed increase of the real exchange rate volatility with respect to output in the last 20 year can be explained by changes in the parameter of the VECM.
This paper uses a vector autoregression (VAR) approach to identify the driving forces of the growth slowdown in Japan during the 1990s. Negative shocks to both residential and nonresidential investment are shown to have been important determinants of the slowdown. Despite the collapse in asset prices, negative shocks to private consumption were relatively small. A surprising conclusion is that trends in public consumption had a dampening impact on activity in the 1990s. The VAR estimations do not support the counterfactual conjecture that activity in Japan would have been significantly weaker in the absence of the expansionary shift in fiscal policy.