Monetary policy and food inflation in South Africa: A quantile regression analysis

Although optimal monetary policy stabilizes food inflation theoretically, empirical studies remain limited not only in the context of volumes and the estimation approaches, but are focused on selected advanced and emerging countries to the neglect of Africa where poverty and dominance of food in the consumption basket are more pronounced. We provide empirical evidence in the context of South Africa using quantile regressions. Rising food prices are destabilized even further by restrictive monetary policy; a finding that has ramifications for inflation targeting, especially given that a quarter of the country’s population is food poor.     

Forecasting the UK economy with a medium-scale Bayesian VAR

We estimate a Bayesian VAR (BVAR) for the UK economy and assess its performance in forecasting GDP growth and CPI inflation in real time relative to forecasts from COMPASS, the Bank of England’s DSGE model, and other benchmarks. We find that the BVAR outperformed COMPASS when forecasting both GDP and its expenditure components. In contrast, their performances when forecasting CPI were similar. We also find that the BVAR density forecasts outperformed those of COMPASS, despite under-predicting inflation at most forecast horizons. Both models over-predicted GDP growth at all forecast horizons, but the issue was less pronounced in the BVAR. The BVAR’s point and density forecast performances are also comparable to those of a Bank of England in-house statistical suite for both GDP and CPI inflation, as well as to the official Inflation Report projections. Our results are broadly consistent with the findings of similar studies for other advanced economies.     

How artificial intelligence will affect the future of retailing

Artificial intelligence (AI) will substantially impact retailing. Building on past research and from interviews with senior managers, we examine how senior retailing managers should think about adopting AI, involving factors such as the extent to which an AI application is customer-facing, the amount of value creation, whether the AI application is online, and extent of ethics concerns. In addition, we highlight that the near-term impact of AI on retailing may not be as pronounced as the popular press might suggest, and also that AI is likely to be more effective if it focuses on augmenting (rather than replacing) managers’ judgments. Finally, while press coverage typically involves customer-facing AI applications, we highlight that a lot of value can be obtained by adopting non-customer-facing applications. Overall, we remain very optimistic as regards the impact of AI on retailing. Finally, we lay out a research agenda and also outline implications for practice.     

Inflation,real economic growth and unemployment expectations: an empirical analysis based on the ECB survey of professional forecasters

Expectations are at the centre of modern macroeconomic theory and policymakers. In this article, we examine the predictive ability and the consistency properties of macroeconomic expectations using data of the European Central Bank (ECB) Survey of Professional Forecasters (SPF). In particular, we provide evidence on the properties of forecasts for three key macroeconomic variables: the inflation rate, the growth rate of real gross domestic product and the unemployment rate.     

通货膨胀的各种成因及其在我国的实证分析

本文不仅总结了当前主要的实证研究文献提出的我国通货膨胀的种种成因,而且对每种原因给予了比较分析和新的实证分析,并在此基础上尝试进行了综合分析,以得出一些有益的结论。     

Learning and the monetary policy strategy of the European Central Bank

This paper examines the welfare implications of alternative inflation targeting proposals for the monetary policy of the European Central Bank. We assume that policy makers have to “learn” the laws of motion of inflation in an economy characterized by “stickiness” in domestic price setting behavior and subjected to recurring shocks to productivity, exports and foreign price. We find that a switch from an “asymmetric” inflation targeting strategy to an “symmetric” makes little difference in welfare payoffs, but it comes at a cost of much higher interest-rate variability. We also find that there are practically no welfare gains from switching from an inflation-targeting strategy based on the Harmonized Index of Consumer Prices (HICP) to a strategy based on the domestic price component of the HICP.     

Regional integration: an empirical assessment of Russia

Using a statistical model of commodity trade, we quantify the evolution of regional economic integration within Russia during 1995–1999, and explore potential determinants of this evolution. Our integration measure exhibits rich regional variation that, when aggregated to the national level, fluctuates substantially over time. In accounting for this behavior, we draw in part on theoretical models that emphasize the potential role of openness to international trade and regional disparities in income in threatening economic integration. Controlling for a host of additional regional- and national-level variables, we find a strong negative correspondence between openness to international trade and internal economic integration.     

Money, endogenous fertility and economic growth

This paper analyzes the issue of money superneutrality through an intertemporal optimizing model of capital accumulation with endogenous fertility, i.e. endogenous population growth. Two elements of this setup invalidate money superneutrality: (i) a demand for fertility that depends on real money balances, and (ii) an inverse relation between capital–labor ratio and population growth. Higher monetary growth increases fertility, since it reduces its opportunity cost, and hence diminishes capital intensity, and per capita output. This reverse Tobin effect is matched by an increase in aggregate capital and output growth rates. In this framework, the optimal monetary growth rule is a “distorted Friedman rule”.     

基于BP网络对我国通货膨胀率的预测及其分析

本文首先由我国的CPI计算出通货膨胀率,综合分析了我国通货膨胀率和GDP增长率数据。其次,用带有动量项和自适应学习率的BP神经网络预测出2008～2009年我国CPI,从而推算出2008～2009年我国通货膨胀率分别是4.99%和4.91%左右。并提出了一些相应的政策建议。     

Contemporary Extensions of the Rasch Model

This paper will introduce, discuss and illustrate two contemporary extensions of theRasch model: the one parameter logistic model (Verhelst and Glas, 1995) and theMultidimensional Rasch model (Hoijtink et al., 1999). Using data with respect tothe measurement of schizotypy (Vollema and Hoijtink, 2000) the most importantfeatures of both models will be illustrated. For the one parameter logistic modelthese include: a (discrete) discrimination parameter for each item; a test for itembias; and, estimation of the location of a person on the (latent) trait that is beingmeasured. For the multidimensional Rasch model these include: specification ofthe model; and, model selection. All analyses presented in this paper can be executedusing either OPLM (Verhelst et al., 1995), TESTFACT (Wilson et al.,1984) or ConQuest (Wu et al., 1998). At the end of the paper some features ofmodels and software that have not been discussed will be summarized.