LUCA BENATI, European Central Bank (ECB)
Email: Luca.Benati@ecb.int
PAOLO SURICO, London Business School - Department of Economics, Centre for Economic Policy Research (CEPR)

Most analyses of the U.S. Great Moderation have been based on structural VAR methods, and have consistently pointed towards good luck as the main explanation for the greater macroeconomic stability of recent years. Based on an estimated New-Keynesian model in which the only source of change is the move from passive to active monetary policy, we show that VARs may misinterpret good policy for good luck. First, the policy shift is sufficient to generate decreases in the theoretical innovation variances for all series, and decreases in the variances of inflation and the output gap, without any need of sunspot shocks. With sunspots, the estimated model exhibits decreases in both variances and innovation variances for all series. Second, policy counterfactuals based on the theoretical structural VAR representations of the model under the two regimes fail to capture the truth, whereas impulse-response functions to a monetary policy shock exhibit little change across regimes. Since these results are in line with those found in the structural VARbased literature on the Great Moderation, our analysis suggests that existing VAR evidence is compatible with the 'good policy' explanation of the Great Moderation.

NUNO CASSOLA, European Central Bank (ECB)
Email: Nuno.Cassola@ecb.int

The theory of liquidity management under uncertainty predicts that, under certain conditions, commercial banks will accumulate minimum reserve requirements linearly over the reserve maintenance period. This prediction is empirically tested using daily data (from March 2004 until February 2007) on the current accounts and minimum reserve requirements of a panel of 79 commercial banks from the euro area. The linear accumulation hypothesis is not rejected by the data with the exception of small banks which build-up excess reserves. The empirical analysis suggest that idiosyncratic liquidity uncertainty is much higher than aggregate liquidity uncertainty. Nevertheless, on the penultimate day in the reserve maintenance period, the inverse demand schedule of the representative bank is relatively flat around the middle of the interest rate corridor set by the standing facilities. This suggests that liquidity effects on the overnight inter-bank rate should be very muted on this day. Our calibration exercise suggests that the probability of an individual bank's daily overdraft in the euro area is very low (less than 1.0 %). This is confirmed by the analysis of the daily recourses to the marginal lending facility by the panel banks.

TOMMASO PROIETTI, University of Rome II - Dipartimento S.E.F. e Me.Q.
Email: tommaso.proietti@uniroma2.it

The chapter deals with parametric models for the measurement of the business cycle in economic time series. It presents univariate methods based on parametric trend - cycle decompositions and multivariate models featuring a Phillips type relationship between the output gap and inflation and the estimation of the gap using mixed frequency data. We finally address the issue of assessing the accuracy of the output gap estimates.

FRANK LUTGENS, Maastricht University - Faculty of Economics & Business Administration
Email: F.Lutgens@Finance.Unimaas.nl
PETER C. SCHOTMAN, Maastricht University
Email: p.schotman@maastrichtuniversity.nl

We consider mean-variance portfolio choice of a robust investor. The investor receives advice from J experts, each with a different prior for the distribution of returns. Confronted with these multiple priors the investor follows a min-max portfolio strategy. We study the structure of the robust mean-variance portfolio and empirically compare its performance with a variety of alternative portfolio strategies. The empirical tests are based on bootstrap simulations on the 25 Fama-French portfolios and on 81 European country and value portfolios. We find that the robust portfolio performs well in both settings. Robust portfolios do not exhibit the extreme weights typically observed in naive mean-variance portfolios. Robust portfolios are also better diversified than portfolios that impose short-sell constraints to suppress the symptoms of extreme weights.

PAUL J. DEVEREUX, University College Dublin - Department of Economics, Institute for the Study of Labor (IZA)
Email: devereux@ucd.ie

In many economic applications, observations are naturally categorized into mutually exclusive and exhaustive groups. For example, individuals can be classified into cohorts and workers are employees of a particular firm. Grouping models are widely used in economics -- for example, cohort models have been used to study labour supply, wage inequality, consumption, and intergenerational transfer of human capital. The simplest grouping estimator involves taking the means of all variables for each group and then carrying out a group-level regression by OLS or weighted least squares. This estimator is biased in finite samples. I show that the standard errors in variables estimator (EVE) designed to correct for small sample bias is exactly equivalent to the Jack-knife Instrumental Variables Estimator (JIVE). Also EVE is closely related to the k-class of instrumental variables estimators. I then use results from the instrumental variables literature to develop an estimator (UEVE) with better finite-sample properties than existing errors in variables estimators. The theoretical results are demonstrated using Monte Carlo experiments. Finally, I use the estimators to implement a model of inter-temporal male labour supply using micro data from the United States Census. There are sizeable differences in the wage elasticity across estimators, showing the practical importance of the theoretical issues discussed in this paper even in circumstances where the sample size is quite large.

JOHN L. SIMPSON, Curtin University of Technology - School of Economics and Finance
Email: Simpsonj@cbs.curtin.edu.au

Whilst some regional energy markets appear to be integrating, the pricing of natural gas exports in an imperfect global market remains a difficult task. This paper expands a global party to party gas price bargaining model to capture optimally lagged daily price changes of the major competing fuels and daily changes of a global economic indicator in the world stock market price index. Vector autoregressive based tests provide evidence of cointegration. Exogeneity tests show that changes in the daily gas price are primarily driven by changes in the daily oil price. Within this framework it is found that changes in the latter variable are driven significantly by daily changes in global stock price index and coal price index values. This may assist gas producers in both forecasting prices and in their pricing negotiations.

S. K. MISHRA, North-Eastern Hill University (NEHU)
Email: mishrasknehu@hotmail.com

Subjugation of women in certain spheres of life is very common in the patriarchal societies and it has a long history. In India, women have little social or economic independence. They are treated inequitably at home as much as at the workplace outside. Perhaps, it is so for the Indian society is predominantly patriarchal. However, Meghlaya, a state in North East India, presents a case different than what the rest of the country (except Kerala) does. A very large majority of population in the state belongs to three tribes, Garo, Jaintia and Khasi, well known for their being matrilineal and matrifocal (whether effectively matriarchal or not). In this paper we investigate how women in Meghalaya perform, vis-à-vis men, in the socio-economic sphere. The investigation is based on Census of India-2001 data. Two sets of nine variables that measure socio-economic inclusion of people in development have been obtained, the first for men and the second for women, and from these variables a composite index has finally been constructed. In the interim, many methods of constructing a composite index are discussed and applied on the data for obtaining loadings on the variables. Analytic methods (e.g. principal component/factor analysis) and synthetic methods (MSAR, MEFAR and MMAR) have been compared empirically. We find that the synthetic methods perform better than the analytic methods.

Do matriarchal/matrifocal societies favour women in socio-economic sphere and achieve gender equality? We conclude that indeed they do so. The tribes of Meghalaya whose societies are organized on matrifocal/matrilineal principles have obtained much greater gender equality than the societies (e.g. Hindu and Muslim) that are organized on the patriarchal principles.

MARTIN HENRIKSSON, Linkoping University - Center for Medical Technology Assessment (CMT)
Email: martin.henriksson@ihs.liu.se
DAVID M. EPSTEIN, University of York (UK) - Center for Health Economics
Email: dme2@york.ac.uk
STEPHEN PALMER, York University
Email: sjp21@york.ac.uk
MARK SCULPHER, University of York (UK) - Centre for Health Economics
Email: mjs23@york.ac.uk

Background: Event based models are driven by the occurrence of clinical events such as primary clinical endpoints in randomised trials or adverse events associated with treatment. Statistical analyses of individual-patient data are used to determine event rates and further statistical analyses are performed to estimate survival, costs and health-related quality of life conditional on an event having occurred. For economic evaluations of health-care programmes such an approach has several advantages as extrapolation is facilitated, it is possible to explore cost-effectiveness in different risk groups and it makes it possible to bring in relevant external evidence such as pooled treatment effect. However, event based modelling also poses methodological challenges concerning not only technical issues but also conceptual ones regarding the scientific method. The aim of this paper is to explore and discuss these methodological challenges.

Methods: Published event based models were reviewed and examples from a recently developed event based model in acute coronary syndrome were used to discuss and exemplify several of the methodological issues involving event based modelling.

Results: The event based modelling approach normally uses randomised evidence to determine rates of clinical events, but given that an event has occurred, life expectancy, costs and health-related quality of life are estimated conditional on the event rather than randomised treatment. Some would argue this is appropriate as treatment only affect costs and quality of life through the impact of events rates. However, others would argue that such an approach is inappropriate as it adds 'structure' to the randomised evidence in terms of costs, life-expectancy and quality of life assuming conditional independence. Regarding more technical aspects, several methodological issues need to be considered as relatively advanced statistical models are combined in a decision-analytic framework to determine cost-effectiveness. The most important advantage of event based modelling identified in this work is that it provides a tool to estimate cost-effectiveness in a way relevant for policy, i.e. enabling the estimation of lifetime costs and health outcomes in different subgroups utilising all relevant evidence. Some of the challenges identified in this work include the choice of covariates to be included in the statistical analyses and the presentation of the results and probabilistic sensitivity analyses as much of the inputs into the cost-effectiveness model will be based on risk equations which can potentially define a very large number of subgroups.

Conclusion: Although there are still methodological issues that need addressing in this framework, event based modelling is a useful method for providing relevant cost-effectiveness evidence.