Forecasts Of Economic Variables Research Articles

Cognitive Uncertainty

Abstract This article documents the economic relevance of measuring cognitive uncertainty: people’s subjective uncertainty over their ex ante utility-maximizing decision. In a series of experiments on choice under risk, the formation of beliefs, and forecasts of economic variables, we show that cognitive uncertainty predicts various systematic biases in economic decisions. When people are cognitively uncertain—either endogenously or because the problem is designed to be complex—their decisions are heavily attenuated functions of objective probabilities, which gives rise to average behavior that is regressive to an intermediate option. This insight ties together a wide range of empirical regularities in behavioral economics that are typically viewed as distinct phenomena or even as reflecting preferences, including the probability weighting function in choice under risk; base rate insensitivity, conservatism, and sample size effects in belief updating; and predictable overoptimism and -pessimism in forecasts of economic variables. Our results offer a blueprint for how a simple measurement of cognitive uncertainty generates novel insights about what people find complex and how they respond to it.

How can independent fiscal institutions make the most of assessing past economic forecasts?

Forecasts of economic variables like GDP, inflation and unemployment are the starting points for budget planning. Most OECD countries have designated an independent fiscal institutions to scrutinise or endorse the economic forecasts prepared by finance ministries. Although external assessments of past forecast errors can help uncover systematic bias or underperformance in official forecasts, there are several conceptual and practical problems with doing so that limit their usefulness. This paper describes the limitations of ex post forecast assessments and offers some suggestions on how independent fiscal institutions can add the most value in providing them.

The Rationality Of Economic Forecasts: The Cases Of Rubber, Oil Palm, Forestry And Mining Sector

Forecasts of economic variables is very important for planning and policy making purposes. Forecasts is an important input in decision making processes because obtaining reliable forecasts of some relevant macroeconomic variables is necessary for efficient management of funds, time and resources.Business has always recognised the need for a view of the future and has used explicit forecasts in the design and execution of their economic andJor business policies. For example, a firm trying to decide upon its investment programme will have to take into account not only the current known set of circumstances but also the unknown economic and business conditions in the future. The firm has to form a view about the future, such as the likely sales, costs, prices, competitors' reactions, labour requirements, government regulations and so on. These views about the future values of economic variables are frequently referred to as 'expectations', that is, what the firm expects to happen in the future.In recent years the performances of many microeconomics and macroeconomics series have been erratic. For example, rate of inflation, price of crude oil, prices of primary commodities, rate of interest and other pertinent economic variables have been fluctuating widely and have caused concern among the public, politicians, economists and also the businessmen. According to Mayes (l 981), with such non-uniformity of economic variables observed in the last two decades, the role of expectations has become more relevant in the economic agents' decision making process. Mayes (1981) further states that under the present conditions it has become more important to consider what expectations actually are and how they are formed.The value of economic forecasts of certain macroeconomic variables can be derived from several methods. The three main methods for deriving economic forecasts are (i) time series, (ii) econometric models, and (iii) survey of intentions of concerned agents and organizations. Time seriesanalysis and econometric modeling are the two most widely used methods in economic forecasting, but Holden and Peel (1983) had noted their drawbacks. Recently, economists have turned their direction of interest in evaluating the rationality of economic forecasts from surveys of market participants. The empirical literature on the direct tests of the rational expectations hypothesis is vast and growing. Holden et al. (1985), Lovell (1986), Wallis (1989), Maddala (1991) and Pesaran (1991) had reviewed some of these studies. The aim was to determine whether survey data on economic forecasts are accurate in the Muth's (1961) sense, that is, whether participating economic agents used all available information at the time forecasts are made. in other words, the rational expectations hypothesis of the economic forecast was put to test. In general, the empirical studies do not support the rational expectations hypothesis.Most of the studies carried out to evaluate the rationality of business firms' forecasts of economic variables were conducted on developed nations. Madsen (1993) studies the formation of output expectations in manufacturing industry in Japan, Denmark, Finland, France, Germany, Netherlands, Norway, Sweden and the United Kingdom. He found that the rational expectations hypothesis was weakly rejected. Williams (1988) and Chazelas (1988) found investment forecasts biased predictors of the actual investment value for firms in the United Kingdom and France. Meganck et a!. (1988) have concluded that investment forecasts of the manufacturing firm in Belgium were unbiased predictors of the actual values. However. Daub (1982) failed to find any rationality of the Canadian capital investment intention survey data. On the other hand. a study by Leonard (1982) on employment forecasts by the United States services sectors found that the forecasts were biased and the rationality of these employment forecasts rejected.The purpose of this paper is to present some empirical evidence on the rationality of agricultural firm managers' expectations using survey data. This study is important because it adds to the current literature on the testing of rationality of survey data, in particular, it provides empirical evidence from the perspective of a developing country. As for the country under study, the finding of the study could establish whether the forecasts documented by such survey are accurate or not; and if not, ways to produce more accurate forecasts must be found. 'Rationality' in this paper means that managers in agricultural firms have unbiased expectations and efficiently utilised available information at the time the forecasts are made.

Revisiting Targeted Factors

This paper proposes new methods for ‘targeting’ factors estimated from a big dataset. We suggest that forecasts of economic variables can be improved by tuning factor estimates: (i) so that they are both more relevant for a specific target variable; and (ii) so that variables with considerable idiosyncratic noise are down‐weighted prior to factor estimation. Existing targeted factor methodologies are limited to estimating the factors with only one of these two objectives in mind. We therefore combine these ideas by providing new weighted principal components analysis (PCA) procedures and a targeted generalized PCA (TGPCA) procedure. These methods offer a flexible combination of both types of targeting that is new to the literature. We illustrate this empirically by forecasting a range of US macroeconomic variables, finding that our combined approach yields important improvements over competing methods, consistently surviving elimination in the model confidence set procedure. Copyright © 2016 John Wiley & Sons, Ltd.

On the Need for a New Approach to Analyzing Monetary Policy

We present a pricing kernel that summarizes well the main features of the dynamics of interest rates and risk in postwar U.S. data and use it to uncover how the pricing kernel has moved with the short rate in this data. Our findings imply that standard monetary models miss an essential link between the central bank instrument and the economic activity that monetary policy is intended to affect, and thus we call for a new approach to monetary policy analysis. We sketch a new approach using an economic model based on our pricing kernel. The model incorporates the key relationships between policy and risk movements in an unconventional way: the central bank's policy changes are viewed as primarily intended to compensate for exogenous business cycle fluctuations in risk that threaten to push inflation off target. This model, while an improvement on standard models, is considered just a starting point for their revision. It leads to critical questions that researchers need to answer as they continue to revise their approach to monetary policy analysis. Copyright © 2009 by the National Bureau of Economic Research.

Dynamic aspects of air quality control costs

This paper investigates aggregate cost differentials due to implementing environmental regulations over alternative time periods. These differentials may be related t o premature obsolescence of the capital stock, technical advances in abatement, and perhaps other factors. Our estimates, which are subject to a number of qualifications, indicate that these differentials may be substantial. We conduct our investigation within a simple but complete general equilibrium model and contrast our approach with more conventional techniques of forecasting and policy assessment. Our model consists of a description of preferences, technology, and the interaction of economic agents which generates forecasts of economic variables for alternative scenario,.