RePEc: Research Papers in Economics

Research Papers in Economics is a collaborative effort of hundreds of volunteers in many countries to enhance the dissemination of research in economics.

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NCER Working Paper Series

2010

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  • #69
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    Keywords:
    Global Financial Crisis, Great Recession,

    Can We Predict Recessions?

    Don Harding and Adrian Pagan

    The fact that the Global Financial Crisis, and the Great Recession it ushered in, was largely unforeseen, has led to the common opinion that macroeconomic models and analysis is deficient in some way. Of course it has probably always been true that businessmen, journalists and politicians have agreed on the proposition that economists can't forecast recessions. Yet we see an enormous published literature that presents results which suggest it is possible to do so, either with some new model or some new estimation method e.g. Kaufman (2010), Galvao (2006), Dueker (2005), Wright (2006) and Moneta (2005). Moreover, there seem to be no shortage of papers still emerging that make claims along these lines. So a question that naturally arises is how one is to reconcile the existence of an expanding literature on predicting recessions with the scepticism noted above?

  • #68
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    JEL-Codes:
    G32;G35
    Keywords:
    Volatility; Trend; Turnover
    (forthcoming)

    Comparing Different Explanations of the Volatility Trend

    Amir Rubin and Daniel Smith

    We analyze the puzzling behavior of the volatility of individual stock returns over the past few decades. The literature has provided many different explanations to the trend in volatility and this paper tests the viability of the different explanations. Virtually all current theoretical arguments that are provided for the trend in the average level of volatility over time lend themselves to explanations about the difference in volatility levels between firms in the cross-section. We therefore focus separately on the crosssectional and time-series explanatory power of the different proxies. We fail to find a proxy that is able to explain both dimensions well. In particular, we find that Cao et al. (2008) market-to-book ratio tracks average volatility levels well, but has no crosssectional explanatory power. On the other hand, the low-price proxy suggested by Brandt et al. (2010) has much cross-sectional explanatory power, but has virtually no time-series explanatory power. We also find that the different proxies do not explain the trend in volatility in the period prior to 1995 (R-squared of virtually zero), but explain rather well the trend in volatility at the turn of the Millennium (1995-2005).

  • #67
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    JEL-Codes:
    C12;C14;C52,G11
    Keywords:
    Value-at-Risk, Backtesting, Quantile Regression
    (forthcoming)

    Evaluating Value-at-Risk Models via Quantile Regression

    Wagner Piazza Gaglianone, Luiz Renato Lima, Oliver Linton and Daniel Smith

    This paper is concerned with evaluating Value-at-Risk estimates. It is well known that using only binary variables, such as whether or not there was an exception, sacrifices too much information. However, most of the specification tests (also called backtests) available in the literature, such as Christofferson (1998) and Engle and Mangenelli (2004) are based on such variables. In this paper we propose a new backtest that does not rely solely on binary variables. It is shown that the new backtest provides a sufficient condtion to assess the finite sample performance of a quantile model whereas the existing ones do not. The proposed methodolgy allows us to identify periods of an increased risk exposure based on a quantile regression model (Koenker and Xiao, 2002). Our theoretical findings are corroborated through a Monte Carlo simulation and an empirical exercise with daily S&P500 time series.

  • #66
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    JEL-Codes:
    C14, C32, C53, C58
    Keywords:
    Nonparametric, variance-covariance matrix, volatility forecasting, multivariate

    A Kernel Technique for Forecasting the Variance-Covariance Matrix

    Ralf Becker, Adam Clements and Robert O'Neill

    The forecasting of variance-covariance matrices is an important issue. In recent years an increasing body of literature has focused on multivariate models to forecast this quantity. This paper develops a nonparametric technique for generating multivariate volatility forecasts from a weighted average of historical volatility and a broader set of macroeconomic variables. As opposed to traditional techniques where the weights solely decay as a function of time, this approach employs a kernel weighting scheme where historical periods exhibiting the most similar conditions to the time at which the forecast if formed attract the greatest weight. It is found that the proposed method leads to superior forecasts, with macroeconomic information playing an important role.

  • #65
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    JEL-Codes:
    C22;C52
    Keywords:
    stochastic differential equations, parameter estimation, quasi-maximum likelihood, moments

    A quasi-maximum likelihood method for estimating the parameters of multivariate diffusions

    Stan Hurn, Andrew McClelland and Kenneth Lindsay

    This paper develops a quasi-maximum likelihood (QML) procedure for estimating the parameters of multi-dimensional stochastic differential equations. The transitional density is taken to be a time-varying multivariate Gaussian where the first two moments of the distribution are approximately the true moments of the unknown transitional density. For affine drift and diffusion functions, the moments are shown to be exactly those of the true transitional density and for nonlinear drift and diffusion functions the approximation is extremely good. The estimation procedure is easily generalizable to models with latent factors, such as the stochastic volatility class of model. The QML method is as effective as alternative methods when proxy variables are used for unobserved states. A conditioning estimation procedure is also developed that allows parameter estimation in the absence of proxies.

  • #64
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    JEL-Codes:
    G10;G12
    Keywords:
    Realized volatility, bi-power variation, limit order book, market microstructure, order imbalance

    Volatility and the role of order book structure

    Ralf Becker and Adam Clements

    There is much literature that deals with modeling and forecasting asset return volatility. However, much of this research does not attempt to explain variations in the level of volatility. Movements in volatility are often linked to trading volume or frequency, as a reflection of underlying information flow. This paper considers whether the state of an open limit order book influences volatility. It is found that market depth and order imbalance do influence volatility, even in the presence of the traditional volume related variables.

  • #63
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    Keywords:
    Business cycles, binary models, predicting recessions

    Can Turkish Recessions be Predicted?

    Adrian Pagan

    In response to the widespread criticism that macro-economists failed to predict the global recession coming from the GFC, we look at whether recessions in Turkey can be predicted. Because the growth in Turkish GDP is quite persistent one might expect this is possible. But it is the sign of GDP growth that needs to be forecast if we are to predict a recession, and this is made more difficult by the persistence in GDP growth. We build a small SVAR model of the Turkish economy that is motivated by New Keynesian models of the open economy, and find that using the variables entering it increases predictive success, although it is still the case that the predictive record is not good. Non-linear models for Turkish growth are then found to add little to predictive ability. Fundamentally, recession prediction requires one to forecast future shocks to the economy, and thus one needs some indicators of these. The paper explores a range of indicators for the Turkish economy, but none are particularly advantageous. Developing a bigger range of these indicators should be a priority for future Turkish macro-economic research.

  • #62
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    Keywords:
    Rugby league; Rugby Union; favouritism

    Evidence of referees' national favouritism in rugby

    Lionel Page and Katie Page

    The present article reports evidence of national favouritism from professional referees in two major sports: Rugby League and Rugby Union. National favouritism can appear when a referee is in charge of a match where one team (and only one) is from his country. For fear of the risk of such favouritism, such situations are avoided in most major sports. In this study we study two specific competitions who depart from this national neutrality" rule: the European Super League in Rugby League (and its second tier competition) and the Super 14 in Rugby Union. In both cases we find strong evidence that referees favour teams from their own nationality, in a way which has a large influence on match results.
    For these two major competitions, the Super League and the Super 14, we compare how a team performs in situations where the referee both shares their nationality and in situations where the referee comes from a different nationality. We also analyse referees' decisions within matches (such as penalty and try decisions) in a Rugby League competition, the Championship (second tier below the Super League). In both Rugby League and Rugby Union we find strong evidence of national favouritism.

  • #61
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    JEL-Codes:
    C23; L83
    Keywords:
    playoff uncertainty, match uncertainty, sports league attendance, Australian National Rugby League, fixed effects estimation

    Playoff Uncertainty, Match Uncertainty and Attendance at Australian National Rugby League Matches

    Nicholas King, P Dorian Owen and Rick Audas

    This paper develops a new simulation-based measure of playoff uncertainty and investigates its contribution to modelling match attendance compared to other variants of playoff uncertainty in the existing literature. A model of match attendance that incorporates match uncertainty, playoff uncertainty, past home-team performance and other relevant control variables is fitted to Australian National Rugby League data for seasons 2004-2008 using fixed effects estimation. The results suggest that playoff uncertainty and home-team success are more important determinants of match attendance than match uncertainty. Alternative measures of playoff uncertainty based on points behind the leader, although more ad hoc, also appear able to capture the effects of playoff uncertainty.

  • #60
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    JEL-Codes:
    c22;G00
    Keywords:
    Cholesky, Midas, volatility forecasts

    A Cholesky-MIDAS model for predicting stock portfolio volatility

    Ralf Becker, Adam Clements and Robert O'Neill

    This paper presents a simple forecasting technique for variance covariance matrices. It relies significantly on the contribution of Chiriac and Voev (2010) who propose to forecast elements of the Cholesky decomposition which recombine to form a positive definite forecast for the variance covariance matrix. The method proposed here combines this methodology with advances made in the MIDAS literature to produce a forecasting methodology that is flexible, scales easily with the size of the portfolio and produces superior forecasts in simulation experiments and an empirical application.

  • #59
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    JEL-Codes:
    D63;L83
    Keywords:
    sports economics, competitive balance, relative standard deviation,idealized standard deviation, draws/ties

    Measuring Parity in Sports Leagues with Draws: Further Comments

    P Dorian Owen

    This paper re-examines the calculation of the relative standard deviation (RSD) measure of competitive balance in leagues in which draws are possible outcomes. Some key conclusions emerging from the exchange between Cain and Haddock (2006) and Fort (2007) are reversed. There is no difference, for any given points assignment scheme, between the RSD for absolute points compared to percentages of points. However, variations in the points assignment that change the ratio of points for a win compared to a draw do result in different RSD values, although the numerical differences are minor.

  • #58
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    JEL-Codes:
    C22;C53;E32;E37
    Keywords:
    Generalized dynamic categorical model, Business cycle; binary variable, Markov process, probit model, yield curve

    Applying shape and phase restrictions in generalized dynamic categorical models of the business cycle

    Don Harding

    To match the NBER business cycle features it is necessary to employ Generalised dynamic categorical (GDC) models that impose certain phase restrictions and permit multiple indexes. Theory suggests additional shape restrictions in the form of monotonicity and boundedness of certain transition probabilities. Maximum likelihood and constraint weighted bootstrap estimators are developed to impose these restrictions. In the application these estimators generate improved estimates of how the probability of recession varies with the yield spread.

  • #57
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    JEL-Codes:
    E32;C51;C32
    Keywords:
    Structural Vector Autoregressions, New Keynesian Model, Sign Restrictions

    Sign Restrictions in Structural Vector Autoregressions: A Critical Review

    Renee Fry and Adrian Pagan

    The paper provides a review of the estimation of structural VARs with sign restrictions. It is shown how sign restrictions solve the parametric identification problem present in structural systems but leave the model identification problem unresolved. A market and a macro model are used to illustrate these points. Suggestions have been made on how to find a unique model. These are reviewed, along with some of the difficulties that can arise in how one is to use the impulse responses found with sign restrictions.

  • #56
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    JEL-Codes:
    C1; C32; G14
    Keywords:
    US Treasury markets, high frequency data, cojump test

    Cojumping: Evidence from the US Treasury Bond and Futures Markets

    Mardi Dungey and Lyudmyla Hvozdyk

    The basis between spot and future prices will be affected by jump behavior in each asset price, challenging intraday hedging strategies. Using a formal cojumping test this paper considers the cojumping behavior of spot and futures prices in high frequency US Treasury data. Cojumping occurs most frequently at shorter maturities and higher sampling frequencies. We find that the presence of an anticipated macroeconomic news announcement, and particularly non-farm payrolls, increases the probability of observing cojumps. However, a negative surprise in non-farm payrolls, also increases the probability of the cojumping tests being unable to determine whether jumps in spots and futures occur contemporaneously, or alternatively that one market follows the other. On these occasions the market does not clearly signal its short term pricing behavior.

  • #55
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    JEL-Codes:
    C93
    Keywords:
    Tournament, first-mover advantage, psychological pressure, field experiment, soccer, penalty shootouts

    Psychological pressure in competitive environments: Evidence from a randomized natural experiment: Comment

    Martin G. Kocher, Marc V. Lenz and Matthias Sutter

    Apesteguia and Palacios-Huerta (forthcoming) report for a sample of 129 shootouts from various seasons in ten different competitions that teams kicking first in soccer penalty shootouts win significantly more often than teams kicking second. Collecting data for the entire history of six major soccer competitions we cannot replicate their result. Teams kicking first win only 53.4% of 262 shootouts in our data, which is not significantly different from random. Our findings have two implications: (1) Apesteguia and Palacios-Huerta's results are not generally robust. (2) Using specific subsamples without a coherent criterion for data selection might lead to non-representative findings.

  • #54
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    JEL-Codes:
    C22; G11;G17
    Keywords:
    Volatility, utility, portfolio allocation, realized volatility, MIDAS

    Portfolio allocation: Getting the most out of realised volatility

    Adam Clements and Annastiina Silvennoinen

    Recent advances in the measurement of volatility have utilized high frequency intraday data to produce what are generally known as realised volatility estimates. It has been shown that forecasts generated from such estimates are of positive economic value in the context of portfolio allocation. This paper considers the link between the value of such forecasts and the loss function under which models of realised volatility are estimated. It is found that employing a utility based estimation criteria is preferred over likelihood estimation, however a simple mean squared error criteria performs in a similar manner. These findings have obvious implications for the manner in which volatility models based on realised volatility are estimated when one wishes to inform the portfolio allocation decision.

  • #53
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    JEL-Codes:
    C51; E31; E52
    Keywords:
    Monetary Policy, Bank Credit, VAR, Brazil, Chile

    The Credit Channel and Monetary Transmission in Brazil and Chile: A Structured VAR Approach

    Luis Catão and Adrian Pagan

    We use an expectation-augmented SVAR representation of an open economy New Keynesian model to study monetary transmission in Brazil and Chile. The underlying structural model incorporates key structural features of Emerging Market economies, notably the role of a bank-credit channel. We find that interest rate changes have swifter effects on output and inflation in both countries compared to advanced economies and that exchange rate dynamics plays an important role in monetary transmission, as currency movements are highly responsive to changes in in policy-controlled interest rates. We also find the typical size of credit shocks to have large effects on output and inflation in the two economies, being stronger in Chile where bank penetration is higher.