Minsky Goes to Buffalo—and Takes on the Economics Establishment

This essay is based on remarks presented by the author at The Fourth Bi-Annual Cross-Border Post Keynesian Conference, Buffalo State College, on October 9, 2009. It addresses the economic challenges facing Buffalo, New York, and countless other American cities, especially in the Northeast and Midwest; draws on the writings of Hyman Minsky to offer an interpretation of what many now call the Great Recession, which began in late 2007; and challenges the image of Minsky presented by mainstream economists and journalists, with special attention to a recent lecture by Paul Krugman. The essay closes by returning to Buffalo, where—as Minsky anticipated in the 1990s—the economic fate of working families depends largely on the outcome of a national struggle over the shape of future U.S. economic transformation.     

Does a factor Phillips curve help? An evaluation of the predictive power for U.S. inflation

This article evaluates various models’ predictive power for U.S. inflation rate using a simulated out-of-sample forecasting framework. The starting point is the traditional unemployment Phillips curve. We show that a factor Phillips curve model is superior to the traditional Phillips curve, and its performance is comparable to other factor models. We find that a factor AR model is superior to the factor Phillips curve model, and is the best bivariate or factor model at longer horizons. Finally, we investigate a New Keynesian Phillips curve model, and find that its forecasting performance dominates all other models at the longer horizons.     

Building Societies

The following articles appeared in ‘The Guardian’ on 9 May 1983, and are reproduced by kind permission of the Editor. They examine how the position of building societies has changed, how well the societies are coping with this and how adequate and efficient the services that the building societies offer their customers are now proving.     

The impact of B Corp certification on financial stability: Evidence from a multi-country sample

B Corps are firms certified by the non-profit B Lab for pursuing both economic and non-economic goals. Whether B Corps realize a higher financial performance has met mixed evidence. Drawing on the stability-change framework, we ask whether B Corp certification is associated with the level and volatility of financial performance. Also, expecting a greater focus on non-economic activities after certification, equity ratio may decline as shareholders may question the increased non-economic focus. Using nearest neighbor propensity score matched pair method, we draw on a multi-country sample of 355 B Corps and 623 non-B Corps. Our findings are not encouraging. B Corp certification does not provide financial gains nor financial stability, and equity ratio declines and becomes more volatile following certification. Our findings paint a gloomy picture of limited economic benefits and declining participation of equity holders following B Corp certification.     

Premium setting and bank behavior in a voluntary deposit insurance scheme

This study analyzes the effect of premium rates on banks’ incentives to join a deposit insurance scheme and their incentives to invest in risky projects under a voluntary deposit insurance scheme. We find that in order to maximize social welfare, the insurance agency must either set the premium rate to be low so as to attract all banks to join the insurance scheme, or not to have the deposit insurance at all. However, the low premium rate in the voluntary scheme does not balance the budget of the deposit insurance. We also show that in the compulsory deposit insurance scheme, however, it is possible to impose an optimal premium rate that can balance the insurance agency’s budget and achieve the highest social welfare. The results also present the dominance of the compulsory scheme over the voluntary scheme in terms of maximizing social welfare and balancing the budget.

A robust VaR model under different time periods and weighting schemes

This paper analyses several volatility models by examining their ability to forecast Value-at-Risk (VaR) for two different time periods and two capitalization weighting schemes. Specifically, VaR is calculated for large and small capitalization stocks, based on Dow Jones (DJ) Euro Stoxx indices and is modeled for long and short trading positions by using non parametric, semi parametric and parametric methods. In order to choose one model among the various forecasting methods, a two-stage backtesting procedure is implemented. In the first stage the unconditional coverage test is used to examine the statistical accuracy of the models. In the second stage a loss function is applied to investigate whether the differences between the models, that calculated accurately the VaR, are statistically significant. Under this framework, the combination of a parametric model with the historical simulation produced robust results across the sample periods, market capitalization schemes, trading positions and confidence levels and therefore there is a risk measure that is reliable.

The role of stochastic volatility and return jumps: reproducing volatility and higher moments in the KOSPI 200 returns dynamics

This paper investigates the role of stochastic volatility and return jumps in reproducing the volatility dynamics and the shape characteristics of the Korean Composite Stock Price Index (KOSPI) 200 returns distribution. Using efficient method of moments and reprojection analysis, we find that stochastic volatility models, both with and without return jumps, capture return dynamics surprisingly well. The stochastic volatility model without return jumps, however, cannot fully reproduce the conditional kurtosis implied by the data. Return jumps successfully complement this gap. We also find that return jumps are essential in capturing the volatility smirk effects observed in short-term options.

Minimal Hellinger martingale measures of order <Emphasis Type="Italic">q</Emphasis>

This paper proposes an extension of the minimal Hellinger martingale measure (MHM hereafter) concept to any order q≠1 and to the general semimartingale framework. This extension allows us to provide a unified formulation for many optimal martingale measures, including the minimal martingale measure of Föllmer and Schweizer (here q=2). Under some mild conditions of integrability and the absence of arbitrage, we show the existence of the MHM measure of order q and describe it explicitly in terms of pointwise equations in ? ^d . Applications to the maximization of expected power utility at stopping times are given. We prove that, for an agent to be indifferent with respect to the liquidation time of her assets (which is the market’s exit time, supposed to be a stopping time, not any general random time), she is forced to consider a habit formation utility function instead of the original utility, or equivalently she is forced to consider a time-separable preference with a stochastic discount factor.     

Information effects of dividends: Evidence from the Hong Kong market

The literature has suggested that earnings and earnings forecasts provide stronger signals than dividends about future performance of a firm. We test the information effects of simultaneous announcement of earnings and dividends in the Hong Kong market, distinguished by three interesting features (concentrated family-shareholdings, low corporate transparency, and no tax on dividends). Our results show significant share price reactions to unexpected earnings and dividend changes, but dividends appear to play a dominant role over earnings in pricing, a result contrary to findings in the literature. The signaling hypothesis works primarily for firms with earning increases, while the maturity hypothesis works mainly for firms with earnings declines.

The contextual nature of the predictive power of statistically-based quarterly earnings models

We present new empirical evidence on the contextual nature of the predictive power of five statistically-based quarterly earnings expectation models evaluated on a holdout period spanning the twelve quarters from 2000–2002. In marked contrast to extant time-series work, the random walk with drift (RWD) model provides significantly more accurate pooled, one-step-ahead quarterly earnings predictions for a sample of high-technology firms (n = 202). In similar predictive comparisons, the Griffin-Watts (GW) ARIMA model provides significantly more accurate quarterly earnings predictions for a sample of regulated firms (n = 218). Finally, the RWD and GW ARIMA models jointly dominate the other expectation models (i.e., seasonal random walk with drift, the Brown-Rozeff (BR) and Foster (F) ARIMA models) for a default sample of firms (n = 796). We provide supplementary analyses that document the: (1) increased frequency of the number of loss quarters experienced by our sample firms in the holdout period (2000–2002) vis-à-vis the identification period (1990–1999); (2) reduced levels of earnings persistence for our sample firms relative to earnings persistence factors computed by Baginski et al. (2003) during earlier time periods (1970s–1980s); (3) relative impact on the predictive ability of the five expectation models conditioned upon the extent of analyst coverage of sample firms (i.e., no coverage, moderate coverage, and extensive coverage); and (4) sensitivity of predictive performance across subsets of regulated firms with the BR ARIMA model providing the most accurate predictions for utilities (n = 87) while the RWD model is superior for financial institutions (n = 131).

---