Survey Expectations

This paper focuses on survey expectations and discusses their uses for testing and modeling of expectations.Alternative models of expectations formation are reviewed and the importance of allowing for heterogeneity of expectations is emphasized. A weak form of the rational expectations hypothesis which focuses on average expectationsrather than individual expectations is advanced. Other models of expectations formation, such as the adaptive expectations hypothesis, are briefly discussed. Testable implications of rational and extrapolative models of expectationsare reviewed and the importance of the loss function for the interpretation of the test results is discussed. The paper thenprovides an account of the various surveys of expectations, reviews alternative methods of quantifying the qualitative surveys, and discusses the use of aggregate and individual survey responses in the analysis of expectations and for forecasting

Adaptive Forecasting of Exchange Rates with Panel Data

This article investigates the statistical and economic implications of adaptive forecasting of exchange rates with panel data and alternative predictors. The candidate exchange rate predictors are drawn from (i) macroeconomic 'fundamentals', (ii) return/volatility of asset markets and (iii) cyclical and confidence indices. Exchange rate forecasts at various horizons are obtained from each of the potential predictors using single market, mean group and pooled estimates by means of rolling window and recursive forecasting schemes. The capabilities of single predictors and of adaptive techniques for combining the generated exchange rate forecasts are subsequently examined by means of statistical and economic performance measures. The forward premium and a predictor based on a Taylor rule yield the most promising forecasting results out of the macro 'fundamentals' considered. For recursive forecasting, confidence indices and volatility in-mean yield more accurate forecasts than most of the macro 'fundamentals'. Adaptive forecast combinations techniques improve forecasting precision and lead to better market timing than most single predictors at higher horizons.exchange rate forecasting; panel data; forecast combinations; market timing

Business Survey Data: Do They Help in Forecasting the Macro Economy?

In this paper we examine whether data from business tendency surveys are useful for forecasting the macro economy in the short run. Our analyses primarily concern the growth rates of real GDP but we also evaluate forecasts of other variables such as unemployment, price and wage inflation, interest rates, and exchange-rate changes. The starting point is a so-called dynamic factor model (DFM), which is used both as a framework for dimension reduction in forecasting and as a procedure for filtering out unimportant idiosyncratic noise in the underlying survey data. In this way, it is possible to model a rather large number of noise-reduced survey variables in a parsimoniously parameterised vector autoregression (VAR). To assess the forecasting performance of the procedure, comparisons are made with VARs that either use the survey variables directly, are based on macro variables only, or use other popular summary indices of economic activity. As concerns forecasts of GDP growth, the procedure turns out to outperform the competing alternatives in most cases. For the other macro variables, the evidence is more mixed, suggesting in particular that there often is little difference between the DFM-based indicators and the popular summary indices of economic activity.Business survey data; Dynamic factor models; Macroeconomic forecasting

Forecasting Inflation and GDP growth: Comparison of Automatic Leading Indicator (ALI) Method with Macro Econometric Structural Models (MESMs)

This paper compares forecast performance of the ALI method and the MESMs and seeks ways of improving the ALI method. Inflation and GDP growth form the forecast objects for comparison, using data from China, Indonesia and the Philippines. The ALI method is found to produce better forecasts than those by MESMs in general, but the method is found to involve greater uncertainty in choosing indicators, mixing data frequencies and utilizing unrestricted VARs. Two possible improvements are found helpful to reduce the uncertainty: (i) give theory priority in choosing indicators and include theory-based disequilibrium shocks in the indicator sets; and (ii) reduce the VARs by means of the general→specific model reduction procedure.Dynamic factor models, Model reduction, VAR

Fiscal forecasting: lessons from the literature and challenges

While fiscal forecasting and monitoring has its roots in the accountability of governments for the use of public funds in democracies, the Stability and Growth Pact has significantly increased interest in budgetary forecasts in Europe, where they play a key role in the EU multilateral budgetary surveillance. In view of the increased prominence and sensitivity of budgetary forecasts, which may lead to them being influenced by strategic and political factors, this paper discusses the main issues and challenges in the field of fiscal forecasting from a practitioner’s perspective and places them in the context of the related literature. JEL Classification: H6, E62, C53Fiscal policies, forecasting, government budget, monitoring

On the performance of US fiscal forecasts : government vs. private information

This paper contributes to shed light on the quality and performance of US fiscal forecasts. The first part inspects the causes of official (CBO) fiscal forecasts revisions between 1984 and 2016 that are due to technical, economic or policy reasons. Both individual and cumulative means of forecast errors are relatively close to zero, particularly in the case of expenditures. CBO averages indicate net average downward revenue and expenditure revisions and net average upward deficit revisions. Focusing on the causes of the technical component, we uncover that its revisions are quite unpredictable which casts doubts on inferences about fiscal policy sustainability that rely on point estimates. Comparing official with private-sector (Consensus) forecasts, despite the informational advantages CBO might have, one cannot unequivocally say that one or the other is more accurate. Evidence also seems to suggest that CBO forecasts are consistently heavily biased towards optimism while this is less the case for Consensus forecasts. Not only is the extent of information rigidity is more prevalent in CBO forecasts, but evidence also seems to indicate that Consensus forecasts dominate CBO’s in terms of information content.info:eu-repo/semantics/publishedVersio

The economic impact of demographic structure in OECD countries

We examine the impact of demographic structure, the proportion of the population in each age group, on growth, savings, investment, hours, interest rates and inflation using a panel VAR estimated from data for 20 OECD economies, mainly for the period 1970-2007. This flexible dynamic structure with interactions among the main macroeconomic variables allows us to estimate long-run effects of demographic structure on the individual countries. Our estimates confirm the importance of these effects