Risk and Uncertainty: Macroeconomic Perspective (original) (raw)
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ARE EMPIRICAL MEASURES OF MACROECONOMIC UNCERTAINTY ALIKE
Journal of Economic Surveys, 2011
Abstract There is a plethora of time series measures of uncertainty for inflation and real output growth in empirical studies but little is known whether they are comparable to the uncertainty measure reported by individual forecasters in the survey of professional forecasters. Are these two measures of uncertainty inherently distinct? This paper shows that, compared with many uncertainty proxies produced by time series models, the use of real-time data with fixed-sample recursive estimation of an asymmetric bivariate generalized autoregressive conditional heteroskedasticity model yields inflation uncertainty estimates which resemble the survey measure. There is, however, overwhelming evidence that many of the time series measures of growth uncertainty exceed the level of uncertainty obtained from survey measure. Our results highlight the relative merits of using different methods in modelling macroeconomic uncertainty which are useful for empirical researchers.
Assessment of GDP forecast uncertainty
2003
This paper develops an approach to measure the uncertainty surrounding expected GDP growth that prevails in the economy. This is accomplished by making use of consensus forecasts of GDP growth and by studying the properties of distributions of forecasted euro area GDP growth. A euro area distribution is constructed from the mean distributions of individual country specific consensus forecasts. Information contained in the distributions can be used to make uncertainty assessments of future economic development. The paper shows that uncertainty varies over time, and how the levels can be compared with a historical mean and between different time periods. Furthermore, the paper shows that the constructed distributions can be asymmetric as measured by their skewness. This information can be used to assess whether risks are on the upside, or the downside. Two graphs are proposed to be used as a regular monitoring tool, illustrating the measured uncertainty and balance of risks.
Measuring uncertainty and assessing its predictive power in the euro area
Empirical Economics, 2016
Expectations and uncertainty play a key role in economic behavior. This paper deals with both, expectations and uncertainty derived from the European Central Bank Survey of Professional Forecasters. Given the strong turbulences that the euro area macroeconomic indicators observe since 2007, the aim of the paper is to check whether there is any room for improvement of the consensus forecast accuracy for GDP growth and inflation when accounting for uncertainty. We propose a new measure of uncertainty, alternative to the ad hoc equal weights commonly used, based on principal components. We test the role of uncertainty in forecasting macroeconomic performance in the euro area between 2005 and 2015. We also check the role of surprises in the considered forecasting sample. The contents of this publication do not necessarily reflect the position or opinion of the European Commission. The work was initiated while the first author was still at Universidad Autónoma de Madrid and while the second author was visiting the Department of Economics at SUNY University at Albany. The authors gratefully acknowledge the comments received from Kajal Lahiri and an anonymous referee; however, any remaining errors are our own. Financial support from the Spanish Ministry of Economy and Competitiveness, project numbers ECO2015-70331-C2-1-R, ECO2015-66593-P and ECO2014-56676C2-2-P and Universidad de Alcalá is acknowledged.
Forecast Uncertainties in Macroeconomic Modeling
Journal of the American Statistical Association, 2003
This paper argues that probability forecasts convey information on the uncertainties that surround macro-economic forecasts in a straightforward manner which is preferable to other alternatives, including the use of confidence intervals. Probability forecasts obtained using a small benchmark macroeconometric model as well as a number of other alternatives are presented and evaluated using recursive forecasts generated over the period 1999q1-2001q1. Out of sample probability forecasts of inflation and output growth are also provided over the period 2001q2-2003q1, and their implications discussed in relation to the Bank of England's inflation target and the need to avoid recessions, both as separate events and jointly. The robustness of the results to parameter and model uncertainties is also investigated by a pragmatic implementation of the Bayesian model averaging approach.
Gaging the Uncertainty of the Economic Outlook from Historical Forecasting Errors
SSRN Electronic Journal, 2007
Participants in meetings of the Federal Open Market Committee (FOMC) regularly produce individual projections of real activity and inflation that are published in summary form. These summaries indicate participants' views about the most likely course for the macroeconomy but, by themselves, are not enough to gauge the full range of possible outcomes-that is, the uncertainty surrounding the outlook. To this end, FOMC participants will now provide qualitative assessments of how they view the degree of current uncertainty relative to that which prevailed on average in the past. This paper discusses a method for gauging the average magnitude of historical uncertainty using information on the predictive accuracy of a number of private and government forecasters. The results suggest that, if past performance is a reasonable guide to the accuracy of future forecasts, considerable uncertainty surrounds all macroeconomic projections, including those of FOMC participants.
RePEc: Research Papers in Economics, 2020
This paper develops a macroeconomic uncertainty index based on the methodology proposed by Jurado, Ludvigson, and Ng (2015). Our approach streamlines the computation of the macroeconomic uncertainty index by using a state-space model that allows us to obtain the unforecastable component of the macroeconomic variables used to construct the index and the latent factors. Moreover, we estimate this state-space model by maximum likelihood, obtaining the parameters of the model and the latent factors in one step, which is more efficient, by construction, than a multi-stage estimation. Finally, with the forecast errors of the state-space model, we propose to estimate stochastic volatility models also by maximum likelihood, using a density filter that could be faster than a Bayesian estimation. After showing that our methodology produces reasonable results for the United States, we apply it to compute a macroeconomic uncertainty index for Ecuador. Our estimate is the first of this kind for a developing or middle-income country. The results show that the Ecuadorian economy is more volatile and less predictable during recessions. We also provide evidence that macroeconomic uncertainty is detrimental to economic activity, finding that the responses of non-oil GDP, the unemployment rate, and consumer prices to macro uncertainty shocks are sizable and persistent.
Macroeconomic Uncertainty and Macroeconomic Performance: Are They Related?
The Manchester School, 2005
We use a very general multivariate GARCH-M model and G7 monthly data covering the 1957-2003 period to test for the impact of real and nominal macroeconomic uncertainty on inflation and output growth. Our evidence supports a number of important conclusions. First, in most countries output growth uncertainty is a positive determinant of the output growth rate. Second, there is mixed evidence regarding the effect of inflation uncertainty on inflation and output growth. Hence, uncertainty about the inflation rate is not necessarily detrimental to economic growth. Finally, there is mixed evidence on the effect of output uncertainty on inflation.
Measuring Uncertainty: An Indian Perspective
RBI Bulletin, , 2023
Drawing on responses from the survey of professional forecasters (SPF), a measure of uncertainty is constructed, incorporating both common and idiosyncratic sources of risk. Uncertainty was high during 2008 till 2013-14 but it started to decline thereafter and remained subdued till 2019-20. It increased in the wake of the COVID-19 pandemic but ebbed from 2022. Common temporal uncertainty is the major contributor to macroeconomic uncertainty.
2015
It is conjectured that the ex-post inflation forecast uncertainty can be used as a proxy for macroeconomic uncertainty in countries with moderate and high inflation. We argue that the current practice of assessing macroeconomic uncertainty by a count of articles with words related to uncertainty in newspapers might not be adequate. In this study, we have computed ex-post inflation uncertainty for Poland, Russia and Ukraine, with U.S. as a benchmark. The data for annual inflation are monthly and cover the period from 1994until 2014. We derive measures of inflation uncertainty from a skew normal distribution fitted to ex-post (pseudo out of sample) forecast errors. It is shown, by Monte Carlo experiments, that different types of skew-normal distributions fitted to data might give similar results, making identification of the true distribution difficult. We suggest the weighted skew-normal (WSN) distribution as the approximation to the distribution of expost inflation uncertainty. The ...
Measuring Macroeconomic Uncertainty in Zimbabwe
Research Papers in Economics, 2019
What matters to economic decision-making is whether the economy has become more or less predictable. People and businesses use information around them to form judgements about what might happen in the future. The rise in uncertainty might be associated with increased concern about extreme events, skewed towards worries about bad or disastrous events. The study seeks to measure macroeconomic uncertainty in Zimbabwe, using stock market indices-industrial index and mining index-for the period 2010M1 to 2019M3. Prevalence of macroeconomic uncertainty has been traced from the stock market index trend and stock market returns volatility. The squared residuals of the GARCH(1,1) regression model proxied macroeconomic uncertainty levels. The prevalence of significant macroeconomic uncertainty has been observed, with some periods highly uncertain. The study linked periods of uncertainty to some known political, social and economic events to derive meaning. The study found that some political, social and economic events have a contributing effect on the level of macroeconomic uncertainty. Good events and policies are accompanied by low levels of uncertainty while bad events and controversial policies match with high levels of uncertainty. The study recommends that to create a good economic climate, to attract investment and boost confidence in the economy, policymakers should dwell on reducing macroeconomic uncertainty. Reducing macroeconomic uncertainty require policy consistency, policy consultations, less frequent policy changes, avoiding numerous policies, avoiding policy reversals, among other measures. The observed macroeconomic uncertainty affects proper economic decision-making and is not conducive for high levels of investment for local and international investors; companies may struggle to hire labor, and employees and corporates may delay spending and saving pattern distorted.