A Note on Forecasting the Euro: Do Forecasters Have an Asymmetric Loss Function?

Based on the approach advanced by Elliott, Komunjer, and Timmermann (2005 Elliott, G., Komunjer, I., & Timmermann, A. (2005). Estimation and testing of forecast rationality under flexible loss. Review of Economics Studies, 72, 1107–1125. doi: 10.1111/0034-6527.00363[Crossref], [Web of Science ®] , [Google Scholar]), we analyzed whether the loss function of a sample of exchange-rate forecasters is asymmetric in the forecast error. Using forecasts of the dollar/euro exchange rate, we found that the shape of the loss function varies across forecasters. Some forecasters appear to make forecasts under an asymmetric loss function, while a symmetric loss function seems to describe well the loss function of other forecasters. Accounting for an asymmetric loss function does not necessarily make forecasts ‘look’ rational.     

Do Current Account Forecasters Herd? Evidence from the Euro Area and the G7 Countries

Data from the Consensus Economics Forecast Poll is used to analyze how current account forecasters form expectations. The results suggest that forecasts do not satisfy traditional unbiasedness and orthogonality criteria for forecast rationality. In addition, this paper finds anti‐herding behavior among forecasters for the euro area and G7 countries. It also shows that the cross‐sectional heterogeneity with regard to anti‐herding is associated with cross‐sectional heterogeneity in forecast accuracy. More specifically, this paper finds some evidence indicating that forecasters who tend to herd provide more accurate forecasts than their colleagues who follow an anti‐herding strategy.     

Forecasting in efficient bond markets: Do experts know better?

Term structure theory suggests that bond rates in efficient markets approximately follow a random walk. We show that the random walk forecasts of 10-year U.S. Treasury and Moody's Aaa corporate bond rates for 1988–2005 are generally unbiased. Blue Chip forecasts, however, are both biased and inferior to random walk forecasts. Both models produce unbiased forecasts of the default spread, with the random walk again outperforming the Blue Chip. In addition, Blue Chip fails to accurately predict directional change. Emphasizing that the success of the random walk model is theoretically expected, we discuss why experts fail to beat random walk predictions.     

Forecasting stock returns: Do less powerful predictors help?

This paper proposes a simple but efficient way to improve the predictability of stock returns. Instead of torturously constructing new powerful predictors, we readily select existing predictors that have low correlations and thus provide complementary information. Our forecasting strategy is to use the selected predictors based on a multivariate regression model. In our forecasting strategy, less powerful predictors are also useful for forecasting stock returns if they could provide complementary information. The empirical results show that our forecasting strategy outperforms not only the univariate regression models that use each predictor's information separately but also combination approaches that use all predictors jointly. We also document that our strategy extracts significantly more useful information from the complementary predictors than the competing models. In addition, from an asset allocation perspective, a mean-variance investor realizes substantial economic gains. Furthermore, the evidence based on Monte Carlo simulations supports the feasibility of our forecasting strategy.     

Less planning,more development? Housing and urban reform discourses in Australia

This paper examines how particular interests shape urban policy debate and reform in Australia. With a particular emphasis on proposed planning system reforms in the nation’s largest state of New South Wales, we examine written submissions from development industry sectors, resident groups, and professional associations. We then compare these submissions to government responses, finding these responses heavily reflect industry narratives. In the context of an ongoing microeconomic reform agenda oriented towards deregulation and competition policy, housing development is framed as central to delivering economic growth, while the planning system is portrayed as a constraint holding back investment and new housing production. Through this prism, a series of rhetorical strategies reframe community concerns about housing affordability and the impact of new development to fit the growth agenda, while environmental and social considerations are largely sidelined.     

Gone with the Windfall: How Do Housing Allowances Affect Student Co-residence?

Drawing on five cross-sections of the French Housing Survey,this paper examines the effects on co-residence with their parentsof the extension of housing allowances to students that tookplace between 1991 and 1993. Two effects are found. First housingallowances provide an increased opportunity for students tomove out of their parents' home. Second, the subsidy affectsnot just the decision to move out, but location and housingquality choices. Finally we suggest a model to identify howmuch of the allowance came as a windfall gain to parents. Definingthe windfall gain as being the subsidies distributed to studentswho can study locally and whose choice would have been to liveindependently without the subsidy, we find that as much as halfof the allowance came as a windfall gai to students and theirparents. (JEL H22, H23, I22, I28)     

What Explains Herd Behavior in the Chinese Stock Market?

This article examines the causes of herd behavior in the Chinese stock market. Using the nonlinear model of Chang, Cheng, and Khorana [2000 Chang, E. C., J. W. Cheng, and A. Khorana. “An Examination of Herd Behavior in Equity Markets: An International Perspective.” Journal of Banking and Finance, 24, (2000), pp. 1651–1679.[Crossref], [Web of Science ®] , [Google Scholar]], the authors of this article find robust evidence of herding in both the up and down markets. They contribute to the existing literature by exploring the underlying reasons for herding in China. It is shown that analyst recommendation, short-term investor horizon, and risk are the principal causes of herding. However, the authors cannot find evidence that relates herding to firm size, nor can they detect significant differences in herding between state-owned enterprises and non–state-owned enterprises.     

Do Urban Neighborhoods Benefit from Homeowners? Evidence from Housing Prices

Homeownership is heavily subsidized in most countries. The adverse effects of this policy on economic efficiency and income distribution are well documented in the economics literature. The main argument in favor of subsidizing homeownership is that it creates positive externalities that offset these adverse effects. In this paper, we test whether homeowners create positive externalities that capitalize into housing prices in multi‐storey buildings. Using semi‐parametric hedonic regressions with and without instrumental variables, we find no evidence of positive externalities, although the results with instrumental variables are somewhat imprecise. This result is robust to several sensitivity checks and to a relaxation of the identification assumptions of our instrument using set identification.     

Economic rents in franchising: Do they exist?

This work demonstrates the very existence of economic rents in franchising using, for the first time, the franchisees’ actual financial statements. This finding makes franchising more appealing for applicants and supports the hypothesis that rents are efficient devices to motivate franchisees.     

What determines stock liquidity in Australia?

Using an index of corporate governance quality (CGQ), we provide the first robust evidence of the determinants of stock liquidity in Australia. We assume that CGQ affects stock liquidity because effective governance decreases information asymmetries between insiders (e.g. managers) and outsiders (e.g. investors), as well as among outsiders, by improving information transparency of a firm. Consistent with agency theory, this study, using 435 large capitalization firms over the period from 2001 to 2008, finds a significant positive relationship between CGQ and stock liquidity, suggesting that better governed firms have a higher level of stock liquidity. These findings are robust to alternative proxies of CGQ, stock liquidity and endogeneity bias.     

Bottom-up or direct? Forecasting German GDP in a data-rich environment

In this paper, we investigate whether there are benefits in disaggregating GDP into its components when nowcasting GDP. To answer this question, we conduct a realistic out-of-sample experiment that deals with the most prominent problems in short-term forecasting: mixed frequencies, ragged-edge data, asynchronous data releases and a large set of potential information. We compare a direct leading indicator-based GDP forecast with two bottom-up procedures—that is, forecasting GDP components from the production side or from the demand side. Generally, we find that the direct forecast performs relatively well. Among the disaggregated procedures, the production side seems to be better suited than the demand side to form a disaggregated GDP nowcast.     

Forecasting US consumer price index: does nonlinearity matter?

The objective of this article is to predict, both in sample and out of sample, the consumer price index (CPI) of the US economy based on monthly data covering the period of 1980:1–2013:12, using a variety of linear (random walk (RW), autoregressive (AR) and seasonal autoregressive integrated moving average (SARIMA)) and nonlinear (artificial neural network (ANN) and genetic programming (GP)) univariate models. Our results show that, while the SARIMA model is superior relative to other linear and nonlinear models, as it tends to produce smaller forecast errors; statistically, these forecasting gains are not significant relative to higher-order AR and nonlinear models, though simple benchmarks like the RW and AR(1) models are statistically outperformed. Overall, we show that in terms of forecasting the US CPI, accounting for nonlinearity does not necessarily provide us with any statistical gains.     

Forecasting inflation and tracking monetary policy in the euro area: does national information help?

The ECB target is set in terms of the year on year growth rate of the euro area Harmonized Index of Consumer Prices. Nonetheless, a good deal of attention is given to national data by market analysts when they try to anticipate monetary policy moves. In this paper we use the Generalized Dynamic Factor Model to develop a set of core inflation indicators that, combining national data with area wide information, allow us to answer two related questions. The first is whether country specific data actually bear any relevance for the future path of area wide price growth, over and above that already contained in area wide data. The second is whether to track ECB monetary policy decisions it is useful to take into account national information and not only area wide statistics. Within our empirical framework we find that once area wide information is properly taken into account the contribution of national idiosyncratic developments is negligible.