بررسی اثر سیاست های پولی بر نرخ بیکاری با جایگزینی پیش بینی های تورم
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|26924||2010||17 صفحه PDF||سفارش دهید||محاسبه نشده|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Economic Modelling, Volume 27, Issue 1, January 2010, Pages 237–253
This paper explores the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. We use the inflation forecasts of 8 competing models in a standard Bayesian VAR to analyse the size and the timing of these effects, as well as to quantify the uncertainty relative to the different inflation models under two rules. The results suggest that model uncertainty can be a serious issue and strengthen the case for a policy strategy that takes into account several sources of information. We find that combining inflation forecasts from many models not only yields more accurate forecasts than those of any specific model, but also reduces the uncertainty associated with the real effects of policy decisions. These results are in line with the model-combination approach that central banks already follow when conceiving their strategy.
In this paper we investigate the role that inflation forecasts play in the uncertainty surrounding the estimated effects of alternative monetary rules on unemployment dynamics in the euro area and the US. The study focuses on two main issues: the size and timing of the effect of monetary policy on unemployment, and the uncertainty associated with this effect. The effect that a given policy measure might have on unemployment substantially depends on the considerable uncertainty a central bank must cope with when formulating its policy. In this paper we consider model (and parameter) uncertainty, and focus on the uncertainty related to the possibility of correctly predicting the time path of inflation and therefore the price level. Producing comparative evidence on the relative ability of alternative models to forecast inflation helps not only improve the ability of monetary authorities to set interest rates, but also understand the effects of monetary policy on unemployment for each alternative set of forecasts. Our paper explicitly deals with these issues. In particular, we (i) explore the out-of-sample forecast performance of a set of linear and non-linear competing models of inflation rate determination over horizons from 1 to 8 quarters; (ii) evaluate the effect of the policy rate on unemployment in a Bayesian VAR, where the inflation forecast is one of the endogenous variables, and parameter uncertainty is accounted for; (iii) employ standard simulation analysis to quantify the model uncertainty surrounding the estimated effect on unemployment of a shock to the interest rate under two different policy rules. To measure uncertainty, we use the concept of reaction dispersion, similar to the outcome dispersion proposed by Brock et al. (2007). Starting from different model specifications we compute a distribution of possible reactions of unemployment rate to monetary policy shock. The variance of this distribution — which measures the sensitivity of the dynamic response of unemployment to the model choice — is our measure of uncertainty. Model uncertainty plays a dual role here: on the one hand it reflects the choice of the competing models to forecast inflation; on the other hand, we specify two alternative monetary rules, with the central bank reacting either to inflation forecasts and unemployment, or just to inflation. Three main questions are asked in the paper: (i) Can we quantify model uncertainty on the real effects of a monetary policy shock? (ii) Which kind of estimated effect is associated with the best inflation forecast? And (iii) does a forecast combination reduce this uncertainty? The remainder of the paper is structured as follows. Section 2 presents a review of the recent literature. Section 3 analyses the forecasting properties over different horizons of eight competing models by employing alternative econometric techniques. Section 4 examines the role of heterogeneous inflation forecasts on the estimated effects of monetary policy on unemployment, under different monetary policy rules. Section 5 presents empirical measures of model and parameter uncertainty based on the concept of reaction dispersion. Finally, Section 6 summarizes the paper's main findings and their policy implications.
نتیجه گیری انگلیسی
In this paper we have shown how different models for forecasting inflation lead to different estimated effects of monetary policy on unemployment, besides the disparities that could be related to labour market institutions. Our evidence did suggest that the US might have a set of institutions which decreases the persistence of monetary shocks on unemployment, whereas euro area institutions could amplify the persistence of the reaction of unemployment to monetary shocks. However, regardless of the country and of the particular monetary policy rule adopted, a decision based on different inflation forecasts leads to considerable uncertainty regarding its real effects. In order to forecast inflation, we have chosen eight competing models which differ not only in terms of the selected explicative variables and estimation methods, but also in terms of other core assumptions, such as their functional form. A ranking of the models in terms of forecasting performance suggests that there is no single model whose performance is clearly preferred; rather, a combination of forecasts appears most desirable. The inflation forecasts have been used in a standard VAR to quantify the uncertain real effects of a shock to the interest rate under two different policy rules. The results of our paper have three main policy implications. First, our results indicate that combining inflation forecasts from many models yields more accurate forecasts than those of any individual model, for it reduces the uncertainty associated with the estimated effects of policy decisions. Combinations of alternative forecasting models could then provide a benchmark forecast to compare with the judgemental policymaker's forecasts. Second, strict inflation stabilization does not deliver the best monetary policy. In order to reduce the uncertainty associated with a monetary policy shock a central bank should react to both inflation and unemployment rate. Third, the high degree of dispersion across models suggests that the effects of a given policy measure on unemployment are model dependent, and therefore policy decisions should be based on a wide range of possible scenarios in order to overcome policy mistakes. The main message for the policymaker we derive from our empirical investigation is that combining results from alternative representations of the structure of the economy represents a useful strategy to account for model uncertainty when assessing the risks for price stability or when deciding a given policy. In particular, our results can show that a policymaker who selects the results on the basis of a single model might come to misleading conclusions not only about the transmission mechanism but also about the differences between the euro area and the US, which on average are not necessarily large. Clearly one should also be careful in placing too much emphasis on these implications — that are nonetheless in line with current literature (Altavilla and Ciccarelli, in press) — as they stem from an analysis conducted on the Great Moderation sample which can be driving the main results. An interesting extension will be to see how robust are the quantitative and qualitative relationships to a sample change which includes the recent financial turmoil and the global recession.