Combining forecasts: An application to elections

We summarize the literature on the effectiveness of combining forecasts by assessing the conditions under which combining is most valuable. Using data on the six US presidential elections from 1992 to 2012, we report the reductions in error obtained by averaging forecasts within and across four election forecasting methods: poll projections, expert judgment, quantitative models, and the Iowa Electronic Markets. Across the six elections, the resulting combined forecasts were more accurate than any individual component method, on average. The gains in accuracy from combining increased with the numbers of forecasts used, especially when these forecasts were based on different methods and different data, and in situations involving high levels of uncertainty. Such combining yielded error reductions of between 16% and 59%, compared to the average errors of the individual forecasts. This improvement is substantially greater than the 12% reduction in error that had been reported previously for combining forecasts.     

GOVERNMENT SIZE AND GROWTH: A SURVEY AND INTERPRETATION OF THE EVIDENCE

Abstract The literature on the relationship between the size of government and economic growth is full of seemingly contradictory findings. This conflict is largely explained by variations in definitions and the countries studied. An alternative approach – of limiting the focus to studies of the relationship in rich countries, measuring government size as total taxes or total expenditure relative to GDP and relying on panel data estimations with variation over time – reveals a more consistent picture. The most recent studies find a significant negative correlation: an increase in government size by 10 percentage points is associated with a 0.5% to 1% lower annual growth rate. We discuss efforts to make sense of this correlation, and note several pitfalls involved in giving it a causal interpretation. Against this background, we discuss two explanations of why several countries with high taxes seem able to enjoy above average growth. One hypothesis is that countries with higher social trust levels are able to develop larger government sectors without harming the economy. Another explanation is that countries with large governments compensate for high taxes and spending by implementing market‐friendly policies in other areas. Both explanations are supported by ongoing research.     

Economies in Transition: How Important Is Trade Openness for Growth?*

We investigate the effect of trade openness on economic growth in transition countries using a transparent statistical methodology that leads to data‐driven case studies. In particular, we employ synthetic control methods in a panel of transition economies and compare GDP growth in treated (that is, open) countries with growth in a convex combination of similar but untreated (that is, closed) countries. We find that trade liberalization tends to have a positive effect on the pattern of real GDP per capita. One of our most robust results shows that making the transition without opening up to trade considerably hampers growth.     

Accounting als Teil der Management Forschung

PRAXIS | Magazin

Accounting als Teil der Management Forschung Konferenz-Review     

The determinants of commercial banking profitability in low-, middle-, and high-income countries

Using a broad bank-level dataset and the GMM estimator technique described by Arellano and Bover (1995), this paper analyses how bank-specific characteristics, macroeconomic variables, and industry-specific factors affect the profitability of 10,165 commercial banks across 118 countries over the period from 1998 to 2012. Grouping the countries according to three income levels, we show that the determinants of bank profitability included in our model can explain existing profitability differences among commercial banks in low-, middle-, and high-income countries. The profitability determinants vary quite widely across the different levels of income in terms of significance, sign and size of the effect. The level of income has thus an important impact on the determinants of bank profitability.     

Low interest rate policy and the use of reserve requirements in emerging markets

This paper sheds light on the link between the interest rate policy in large advanced economies with international funding and reserve currencies (the United States and the euro area) and the use of reserve requirements in emerging markets. Using reserve requirement data for 28 emerging markets from 1998 to 2012, we provide evidence that emerging market central banks tend to raise reserve requirements when interest rates in international funding markets decline or financial inflows accelerate, most likely to preserve financial stability. In contrast, when global liquidity risk rises and funding from the large advanced economies dries up, emerging markets lower reserve requirements.     

Regional Disparities and Government Quality: Redistributive Conflict Crowds Out Good Government

Abstract

In this paper, we argue and provide empirical evidence to support the claim that higher income differences across regions increase the salience of interregional redistribution and, as a result, crowd out policies aiming towards improvements in government quality or efficiency. In the presence of greater regional disparities, the balance of politics may tilt towards redistributive concerns and away from government efficiency considerations, especially since the latter can be opposed by organized public sector interest groups. Our empirical analysis, based on a sample of 22 Organization for Economic Co-operation and Development (OECD) countries over the period from the mid-1990s to 2005, supports our basic intuition that regional disparities may lead to territorially based redistributive conflict to the detriment of government quality.     

Comparing face-to-face meetings, nominal groups, Delphi and prediction markets on an estimation task

We conducted laboratory experiments for analyzing the accuracy of three structured approaches (nominal groups, Delphi, and prediction markets) relative to traditional face-to-face meetings (FTF). We recruited 227 participants (11 groups per method) who were required to solve a quantitative judgment task that did not involve distributed knowledge. This task consisted of ten factual questions, which required percentage estimates. While we did not find statistically significant differences in accuracy between the four methods overall, the results differed somewhat at the individual question level. Delphi was as accurate as FTF for eight questions and outperformed FTF for two questions. By comparison, prediction markets did not outperform FTF for any of the questions and were inferior for three questions. The relative performances of nominal groups and FTF were mixed and the differences were small. We also compared the results from the three structured approaches to prior individual estimates and staticized groups. The three structured approaches were more accurate than participants’ prior individual estimates. Delphi was also more accurate than staticized groups. Nominal groups and prediction markets provided little additional value relative to a simple average of the forecasts. In addition, we examined participants’ perceptions of the group and the group process. The participants rated personal communications more favorably than computer-mediated interactions. The group interactions in FTF and nominal groups were perceived as being highly cooperative and effective. Prediction markets were rated least favourably: prediction market participants were least satisfied with the group process and perceived their method as the most difficult.