Evaluating the Bank of England density forecasts of inflation

We consider evaluating the UK Monetary Policy Committee's inflation density forecasts using probability integral transform goodness-of-fit tests. These tests evaluate the whole forecast density. We also consider whether the probabilities assigned to inflation being in certain ranges are well calibrated, where the ranges are chosen to be those of particular relevance to the MPC, given its remit of maintaining inflation rates in a band around per annum. Finally, we discuss the decision-based approach to forecast evaluation in relation to the MPC forecasts

Evaluating the Survey of Professional Forecasters probability distributions of expected inflation based on derived event probability forecasts

Techniques are proposed for evaluating forecast probabilities of events. The tools are especially useful when, as in the case of the Survey of Professional Forecasters (SPF) expected probability distributions of inflation, recourse cannot be made to the method of construction in the evaluation of the forecasts. The tests of efficiency and conditional efficiency are applied to the forecast probabilities of events of interest derived from the SPF distributions, and supplement a whole-density evaluation of the SPF distributions based on the probability integral transform approach.

Forecasting with vector autoregressive models of data vintages: US output growth and inflation

Vintage-based vector autoregressive models of a single macroeconomic variable are shown to be a useful vehicle for obtaining forecasts of different maturities of future and past observations, including estimates of post-revision values. The forecasting performance of models which include information on annual revisions is superior to that of models which only include the first two data releases. However, the empirical results indicate that a model which reflects the seasonal nature of data releases more closely does not offer much improvement over an unrestricted vintage-based model which includes three rounds of annual revisions.

Real-time forecasting of inflation and output growth with autoregressive models in the presence of data revisions

We examine how the accuracy of real-time forecasts from models that include autoregressive terms can be improved by estimating the models on ‘lightly revised’ data instead of using data from the latest-available vintage. The benefits of estimating autoregressive models on lightly revised data are related to the nature of the data revision process and the underlying process for the true values. Empirically, we find improvements in root mean square forecasting error of 2–4% when forecasting output growth and inflation with univariate models, and of 8% with multivariate models. We show that multiple-vintage models, which explicitly model data revisions, require large estimation samples to deliver competitive forecasts. Copyright © 2012 John Wiley & Sons, Ltd.

Probability distributions or point predictions? Survey forecasts of US output growth and inflation

We consider whether survey respondents’ probability distributions, reported as histograms, provide reliable and coherent point predictions, when viewed through the lens of a Bayesian learning model. We argue that a role remains for eliciting directly-reported point predictions in surveys of professional forecasters.

US inflation expectations and heterogeneous loss functions, 1968-2010

Recent literature has suggested that macroeconomic forecasters may have asymmetric loss functions, and that there may be heterogeneity across forecasters in the degree to which they weigh under- and over-predictions. Using an individual-level analysis that exploits the Survey of Professional Forecasters respondents’ histogram forecasts, we find little evidence of asymmetric loss for the inflation forecasters

Type-1 error inflation in the traditional by-participant analysis to metamemory accuracy: a generalized mixed-effects model perspective

In order to examine metacognitive accuracy (i.e., the relationship between metacognitive judgment and memory performance), researchers often rely on by-participant analysis, where metacognitive accuracy (e.g., resolution, as measured by the gamma coefficient or signal detection measures) is computed for each participant and the computed values are entered into group-level statistical tests such as the t-test. In the current work, we argue that the by-participant analysis, regardless of the accuracy measurements used, would produce a substantial inflation of Type-1 error rates, when a random item effect is present. A mixed-effects model is proposed as a way to effectively address the issue, and our simulation studies examining Type-1 error rates indeed showed superior performance of mixed-effects model analysis as compared to the conventional by-participant analysis. We also present real data applications to illustrate further strengths of mixed-effects model analysis. Our findings imply that caution is needed when using the by-participant analysis, and recommend the mixed-effects model analysis.

Can British multinational enterprises finance economic development in South East Asia?

Purpose – The purpose of this paper is to shed new light on the debate about the role of foreign direct investment (FDI) and public policy in fostering economic development. Specifically, can the capital inflow of multinational enterprises (MNEs) and the ability of the subsidiaries to raise funds locally help promote development? This paper addresses this issue by examining the capital structure and financing sources of foreign subsidiaries of MNEs. Design/methodology/approach – This paper integrates the capital structure theories in finance with internalization theory in international business. It uses an original primary dataset collected by a survey of 101 foreign subsidiaries of British MNEs in six emerging economies in the ASEAN region. Findings – There are three significant findings. First, these subsidiaries rely heavily on internal funds generated within the MNEs and less on external debts raised in the host countries. Second, the foreign subsidiary's capital structure is influenced by the home country of origin of the parent firm and the parent firm's financing sources. Third, these subsidiaries have used the financial resources to develop business networks with local small and medium enterprises (SMEs) which contribute to economic development of the host countries. Originality/value – This paper examines the internal capital market within the MNE. It provides theoretical and empirical support for the capital structure theory of the hierarchy financing approach and also for internalization theory by addressing FDI inflows by MNEs and the raising of funds locally. These findings have important implications for public policy, namely the facilitation of MNE entry to encourage economic development.

Forecast uncertainty—ex Ante and ex Post: U.S. inflation and output growth

Survey respondents who make point predictions and histogram forecasts of macro-variables reveal both how uncertain they believe the future to be, ex ante, as well as their ex post performance. Macroeconomic forecasters tend to be overconfident at horizons of a year or more, but overestimate (i.e., are underconfident regarding) the uncertainty surrounding their predictions at short horizons. Ex ante uncertainty remains at a high level compared to the ex post measure as the forecast horizon shortens. There is little evidence of a link between individuals’ ex post forecast accuracy and their ex ante subjective assessments.

Asymmetric information, credit market condition, and entrepreneurial finance

The issue of imperfect information plays a much more important role in financing “informationally opaque” small businesses than in financing large companies.1 This chapter examines the asymmetric information issue in entrepreneurial finance from two perspectives: the effects of relationship lending and the impacts of credit market concentration on entrepreneurial financial behavior. These two perspectives are strongly linked to each other via the asymmetric information issue in entrepreneurial finance. Existing literature has recognized the important role played by relationship lending in alleviating the problem of asymmetric information. However, mixed empirical results have been reported. For example, it has been found that the development of relationship lending can improve the availability of finance for small businesses borrowers (Petersen and Rajan, 1994) and reduce the costs of finance (Berger and Udell, 1995). Meanwhile, with monopoly power, banks may extract rents, in terms of charging higher-than-market interest rates, from small businesscustomers who have very concentrated banking relationships (Ongena and Smith, 2001). In addition, both favorable and unfavorable effects of credit market concentration on financing small businesses have been acknowledged. Small business borrowers may have to pay a higher-than-market price on loans (Degryse and Ongena, 2005) and are more likely to be financially constrained (Cetorelli, 2004) than in competitive markets. On the other hand, empirical studies have shown that market concentration create a strong motive for lenders to invest in private information from small business customers, and therefore a concentrated market is more efficient in terms of private information acquisition (Han et al., 2009b). The objective of this chapter is to investigate, by reviewing existing literature, the role played by relationship lending and the effects of market concentration on financing entrepreneurial businesses that are supposed to be informationally opaque. In the first section we review literature on the important role played by asymmetric information in entrepreneurial finance from two perspectives: asymmetric information and relationship lending, and the theoretical modeling of asymmetric information. Then we examine the relationship between capital market conditions and entrepreneurial finance and attempt to answer two questions: Why is the capital market condition important for entrepreneurial finance? and What are the effects of capital market conditions on entrepreneurial financial behavior in terms of discouraged borrowers, cash holding, and the availability and costs of finance?

The Role of Collateral in Entrepreneurial Finance

Previous research has suggested collateral has the role of sorting entrepreneurs either by observed risk or by private information. In order to test these roles, this paper develops a model which incorporates a signalling process (sorting by observed risk) into the design of an incentivecompatible menu of loan contracts which works as a self-selection mechanism (sorting by private information). It then tests this Sorting by Signalling and Self-Selection Model, using the 1998 US Survey of Small Business Finances. It reports for the first time that: high type entrepreneurs are more likely to pledge collateral and pay a lower interest rate; and entrepreneurs who transfer good signals enjoy better contracts than those transferring bad signals. These findings suggest that the Sorting by Signalling and Self-Selection Model sheds more light on entrepreneurial debt finance than either the sorting-by-observed-risk or the sorting-by-private information paradigms on their own.