Forecast quality improvement with Action Research: A success story at PharmaCo

There is a gap in the forecasting research surrounding the theory of integrating and improving forecasting in practice. The number of academically affiliated consultancies and knowledge transfer projects that there are around, due to a need for improvements in forecast quality, would suggest that many interventions and actions are taking place. However, the problems that surround practitioner understanding, learning and usage are rarely documented. This article takes the first step toward trying to rectify this situation by using the specific case study of a fully engaged company. A successful action research intervention in the Production Planning and Control work unit improved the use and understanding of the forecast function, contributing to substantial savings, enhanced communication and improved working practices.     

Measuring Inflation Anchoring and Uncertainty: A U.S. and Euro Area Comparison

We use several U.S. and euro‐area surveys of professional forecasters to estimate a dynamic factor model of inflation featuring time‐varying uncertainty. We obtain survey‐consistent distributions of future inflation at any horizon, both in the U.S. and the euro area. Equipped with this model, we propose a novel measure of the anchoring of inflation expectations that accounts for inflation uncertainty. Our results suggest that following the Great Recession, inflation anchoring improved in the United States, while mild de‐anchoring occurred in the euro area. As of our sample end, both areas appear to be almost equally anchored.     

Unfolding Patterns of Unpaid Household Work in Latin America

Although Colombia, Mexico, Peru, and Uruguay show similar empirical patterns in terms of time women devote to unpaid work, they also present important variations in how unpaid work is distributed between men and women. Using time-use surveys for the 2007–10 period, this study finds a uniform pattern across the four countries regarding the main individual-level variables related to the allocation of unpaid work. When decomposing the gender gap in hours devoted to unpaid work, most of the difference cannot be attributed to variations in observable characteristics of men and women: the unexplained part of the gap is the dominant part. Results suggest that both the strength of traditional gender roles and existing welfare architecture are relevant factors in understanding variations in how unpaid work is distributed between men and women in these four countries. The results reaffirm that powerful interventions are needed to shift gender norms about unpaid work.     

Evaluating FOMC forecasts

Monetary policy outcomes have improved since the early 1980s. One factor contributing to the improvement is that Federal Reserve policymakers began reporting economic forecasts to Congress in 1979. These forecasts indicate what the Federal Open Market Committee (FOMC) members think will be the likely consequence of their policies. We evaluate the accuracy of the FOMC forecasts relative to private sector forecasts, the forecasts of the Research Staff at the Board of Governors, and a naïve alternative. We find that the FOMC output forecasts were better than the naïve model and at least as good as those of the private sector and the Fed staff. The FOMC inflation forecasts were more accurate than the private sector forecasts and the naïve model; for the period ending in 1996, however, they were not as accurate as Fed staff inflation forecasts.     

Sample Design and Allocation for Random Digit Dialling

Sample design and sample allocation methods are developed for random digit dialling in household telephone surveys. The proposed method is based on a two-way stratification of telephone numbers. A weighted probability proportional to size sample allocation technique is used, with auxiliary variables about the telephone coverage rates, within local telephone exchanges of each substrata. This makes the sampling design nearly “self-weighting” in residential numbers when the prior information is well assigned. A computer program generates random numbers for the local areas within the existing phone capacities. A simulation study has shown greater sample allocation gain by the weighted probabilities proportional to size measures over other sample allocation methods. The amount of dialling required to obtain the sample is less than for proportional allocation. A decrease is also observed on the gain in sample allocation for some methods through the increasing sample sizes.     

Terrorism activities and long-term annual management forecasts

We study the effects of terrorist attacks on firms’ long-term annual management earnings forecasts bias. We find that the managers of firms located closer to the epicenters of attacks are more likely to issue optimistic long-term annual earnings forecasts relative to the managers of a control group of unaffected firms. The exposure effect is stronger for more severe terrorist events, and firms with more uncertain fundamentals and less geographic diversification. In addition, we document that managers’ forecast optimism intensifies for firms with stronger negative stock market reaction to the terrorist event, for CEOs with higher ability and for companies that are more likely to issue equity or engage in acquisitions following the terrorist event. Overall, our results are consistent with the idea that long-term annual earnings forecasts are used by managers to counterbalance the short-term pessimistic response to terrorist attacks.     

Nonresponse in Contingent Valuation-reducing uncertainty in value inference

This paper focuses on problems associated with nonresponse in Contingent Valuation surveys. The results from a telephone follow-up survey show that value inference can be considerably improved by information on nonrespondents' attitudes.     

Macroeconomic forecasting using structural factor analysis

The use of a small number of underlying factors to summarize the information from a much larger set of information variables is one of the new frontiers in forecasting. In prior work, the estimated factors have not usually had a structural interpretation and the factors have not been chosen on a theoretical basis. In this paper we propose several variants of a general structural factor forecasting model, and use these to forecast certain key macroeconomic variables. We make the choice of factors more structurally meaningful by estimating factors from subsets of information variables, where these variables can be assigned to subsets on the basis of economic theory. We compare the forecasting performance of the structural factor forecasting model with that of a univariate AR model, a standard VAR model, and some non-structural factor forecasting models. The results suggest that our structural factor forecasting model performs significantly better in forecasting real activity variables, especially at short horizons.     

Interviewers,Interviewer Continuity,and Panel Survey Nonresponse

It is widely known that in practice, different interviewers have different response rates, though there has been no systematic examination of whether this is because of differences among interviewers or differences among those areas allocated to the interviewers (area effects), or both. Furthermore, the conventional wisdom in survey research suggests that it is advisable to have the same interviewers return to the same respondents in order to maintain good response rates in longitudinal surveys, though once again there has been very little documented experimental research to support this. This paper makes use of the interpenetrated sample design experiment in Wave 2 of the British Household Panel Study (BHPS) (i) to explore the effects of interviewers' background characteristics and years of experience on response rates, (ii) to identify and estimate the differential effects of interviewers on response rates and compare the magnitudes of area and interviewer effects, and (iii) to investigate the impact of interviewer continuity. The analysis is facilitated by the use of cross-classified multilevel modelling. The paper also looks at the issue of interviewer continuity qualitatively, through the impressions of the interviewers themselves.     

Seasonal decomposition and forecasting of telecommunication data: A comparative case study

In this paper, forecasting models for the monthly outgoing telephone calls in a University Campus are presented. The data have been separated in the categories of international and national calls as well as calls to mobile phones. The total number of calls has also been analyzed. Three different methods, namely the Seasonal Decomposition, Exponential Smoothing Method and SARIMA Method, have been used. Forecasts with 95% confidence intervals were calculated for each method and compared with the actual data. The outcome of this work can be used to predict future demands for the telecommunications network of the University.