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There exists recent formal theoretical evidence that, relative to true ages, Carbon-14 (¹⁴C) ages for fossils of living organisms (man or animals) are lacking in qualitative and quantitative robustness. This study examines the extent to which highlighted recent evidence extends to ¹⁴C ages for Paper, Ink that is derived from wood, Papyri, and Parchments. The formal axiomatic (mathematically theoretical) evidence establishes, relative to true ages for paper and ink, that ¹⁴C ages for either of paper or ink are qualitatively and quantitatively robust. While ¹⁴C ages for Papyri are not quite as robust as ¹⁴C ages for Paper, formal axioms establish that, asymptotically, and relative to true ages for Papyrus plants, ¹⁴C ages for Papyri are qualitatively and quantitatively robust. While ¹⁴C ages for Parchments originating within the same spatial location are shown to be (asymptotically) qualitatively and quantitatively robust, absent adjustments for spatial differences in rates of young carbon formation, the entire universe of ¹⁴C ages for Parchments is lacking in qualitative and quantitative robustness. The preliminary empirical evidence provides unequivocal support for study predictions. In aggregate, while there exist some concerns about robustness of ¹⁴C ages for Parchments, the evidence reveals boundedness of the concerns, with outcome it safely can be asserted that inferences derived from ¹⁴C ages for Paper, Ink that comes from wood, Papyri, and Parchments can be deemed to be robust.

The present pitch paper intends to pitch the research idea, its methodology, and possible outcomes by following Faff (2015) pitch my research template The rese

This study investigates how commercial paper rates respond to the innovations in stock market risk premiums. The unrestricted vector autoregression (VAR) analysis of monthly data from 1997:1 to 2012:M6 shows that the changes in the one-, two-, and three-month non-financial and financial commercial paper rates positively respond to the innovations in the excess returns on the CRSP value weighted index. The response is especially strong during the first few months following shocks to stock market risk premiums. The Granger-causality test results show the changes in commercial paper rates can be predicted by the excess returns on the CRSP value weighted index. The findings from this study provide evidence that there is a link between equity market and commercial paper market.

We claim that Shiller's analysis of the efficient market variance inequality suffers from statistical and conceptual errors which falsify his conclusions. We detail the errors and provide an analogy to demonstrate them.

We study implications of unpriced "granular measurement errors" -- idiosyncratic shocks to large firms that aren't well-diversified in market indices -- for asset pricing tests and propose alternative tests insensitive to them. We find stronger evidence of an intertemporal relation between the expected return and variance of the market after these corrections. Cross-sectionally, estimated market betas -- especially for small/high beta stocks -- are biased, the size anomaly disappears, and the price of risk for the market portfolio is consistent with theory. The granular residual is volatile and less informative about real activity than our adjusted index, potentially rationalizing lower/zero risk compensation.

This Internet Appendix contains mathematical and empirical results on the market timing induced bias in Jensen’s alpha using conditional models with time-varying skill in the spirit of Kacperczyk et al. (2014).Full paper available at https://ssrn.com/abstract=1253923

Understanding how prior outcomes affect risk attitudes is critical for the study of choice under uncertainty. A large literature documents the influence of prior losses on subsequent risk attitudes. The findings appear contradictory: some studies find that people become more risk seeking after a loss, whereas others assert the opposite -- that they become more risk averse. In this paper, we show that these seemingly inconsistent findings can be explained by individuals' differential responses to realized versus paper losses. Following a realized loss, individuals avoid risk; if the loss has not been realized -- a paper loss -- individuals are more likely to chase their losses and take on even greater risk. We provide support for our framework using existing data and across two experiments. We also show that giving individuals flexibility in choosing when to realize losses can lead to lower earnings in environments where loss-chasing decreases expected returns. Drawing a distinction between paper and realized losses reconciles prior findings, and has important implications for contract design and optimal monitoring.

This paper adumbrates a theory of what might be going wrong in the monetary SVAR literature and provides supporting empirical evidence. The theory is that macroeconomists may be attempting to identify structural forms that do not exist, given the true distribution of the innovations in the reduced-form VAR. The paper shows that this problem occurs whenever (1) some innovation in the VAR has an infinite-variance distribution and (2) the matrix of coefficients on the contemporaneous terms in the VAR’s structural form is nonsingular. Since (2) is almost always required for SVAR analysis, it is germane to test hypothesis (1). Hence, in this paper, we fit a -stable distributions to VAR residuals and, using a parametric-bootstrap method, test the hypotheses that each of the error terms has finite variance.

The paper discusses alternative Research Assessment Measures (RAM), with an emphasis on the Thomson Reuters ISI Web of Science database (hereafter ISI). The various ISI RAM that are calculated annually or updated daily are defined and analysed, including the classic 2-year impact factor (2YIF), 5-year impact factor (5YIF), Immediacy (or zero-year impact factor (0YIF)), Eigenfactor score, Article Influence, C3PO (Citation Performance Per Paper Online), h-index, Zinfluence, and PI-BETA (Papers Ignored - By Even The Authors). The ISI RAM data are analysed for 8 leading econometrics journals and 4 leading statistics journals. The application to econometrics can be used as a template for other areas in economics, for other scientific disciplines, and as a benchmark for newer journals in a range of disciplines. In addition to evaluating high quality research in leading econometrics journals, the paper also compares econometrics and statistics, alternative RAM, highlights the similarities and differences in alternative RAM criteria, finds that several ISI RAM capture similar performance characteristics for the leading econometrics and statistics journals while the new PI-BETA criterion is not highly correlated with any of the other ISI RAM, and hence conveys additional information regarding ISI RAM, highlights major research areas in leading journals in econometrics, and discusses some likely future uses of RAM.

This paper makes an econometric testing of one-minute paper used as a tool to manage and assess instruction in my statistics class. One of our findings is that the one minute paper when I have tested it by using an OLS estimate in a controlled Vs experimental design framework is found to statistically significant and effective in enhancing students’ knowledge. It is found to be equally effective when I have tested it by using a seemingly unrelated regression that allows the error terms to be correlated across separate but related regressions. This is irrespective of students’ ability levels as is measured by GPA in both cases.

This mimeo accompanies the paper by Brailsford, Penm and Terrell titled "The Adjustment of the Yule-Walker Relations in VAR Modeling: The Impact of the Euro on the Hong Kong Stock Market", which was published in Multinational Finance Journal, 5, 1, 35-58, 2001. In response to various matters raised by reviewers, and after further reflection on the original paper, this mimeo has been prepared. It provides supplementary information to that paper, and addresses the following issues: I. Background information on the selection of the optimal zero-non-zero (ZNZ) patterned vector autoregression (VAR) II. Problems of directly extending the use of the Yule-Walker relation for fitting ZNZ patterned VAR models III. Outline of how existing studies ignore the issue of estimating the covariance matrix IV. The standard least squares approach, GLS method and the maximum likelihood approach V. Different studies that employed the Yule-Walker equation to estimate a ZNZ patterned VAR VI. Comparison of the results with and without using the proposed covariance estimator VII. Comments on the example concerning the Hong Kong stock market and the foreign exchange market VIII. Comments on testing for serial correlation in residuals estimated from the ZNZ patterned VAR modelling.

The purpose is to investigate the existence of a causal relationship in organizational levels of slack, risk, and corporate performance. The starting point is the assumption that the amount of organizational slack is a determining factor of risk reflected by the company, as well as of its performance. To test this relationship, we have considered the data of 218 manufacturing companies from 2001 to 2007, a part of these grouped through factorial analysis in such a way as to compose the three kinds of organizational slack under consideration: available, recoverable, and potential. The data were then placed in panel form and analyzed with the GMM. The results obtained confirm the assumption that organizational slack has a non-linear influence on performance.

This paper studies the spillover effect of home mortgage delinquencies using a discrete-choice spatial network model. In our empirical study, a main challenge in estimating this model is that mortgage repayment decisions can only be observed for a sample of all the borrowers in the study region. We show that the nested pseudolikelihood (NPL) algorithm can be readily modified to accommodate this missing data issue. Monte Carlo simulations indicate that the proposed estimator works well in finite samples and ignoring this issue leads to a downward bias in the estimated spillover effect. We estimate the model using data on single-family residential mortgage delinquencies in Clark County of Nevada in 2010, and find strong evidence of spillover effects. We also conduct some counterfactual experiments to illustrate the policy relevance of the spillover effect.

Higher than average Price-to-Earnings (P/E) ratios and Cyclically-Adjusted Price-to-Earnings (CAPE) ratios have been tolerated by investors recently on the basis of low interest and inflation rates. This white paper analyzes what level of returns can reasonably be expected going forward from today’s elevated valuation multiples.

We consider a broad class of intertemporal economic problems and characterize the short-run and long-run responses of the demand for a good to a permanent increase in its market price. Depending on the interplay between self-productivity and time discounting, we show that dynamic substitution effects can generate price elasticities of opposite signs in the short run and in the long run. (JEL D11, D15, H20, J22, J24)

This paper provides invariance theorems that facilitate testing for the existence of an asset price bubble in a market where the price evolves as a Markov diffusion process. The test involves only the properties of the price process’ quadratic variation under the statistical probability. It does not require an estimate of either the equivalent local martingale measure or the asset’s drift. To augment its use, a new family of stochastic volatility price processes is also provided where the processes’ strict local martingale behavior can be characterized.

In this paper we discuss general identification results for Structural Vector Autoregressions (SVARs) with external instruments, considering the case in which r valid instruments are used to identify g Ï 1 structural shocks, where r Ï g. We endow the SVAR with an auxiliary statistical model for the external instruments which is a system of reduced form equations. The SVAR and the auxiliary model for the external instruments jointly form a "larger" SVAR characterized by a particularly restricted parametric structure, and are connected by the covariance matrix of their disturbances which incorporates the "relevance" and "exogeneity" conditions. We discuss identification results and likelihood-based estimation methods both in the "multiple shocks" approach, where all structural shocks are of interest, and in the "partial shock" approach, where only a subset of the structural shocks is of interest. Overidentified SVARs with external instruments can be easily tested in our setup. The suggested method is applied to investigate empirically whether commonly employed measures of macroeconomic and financial uncertainty respond on-impact, other than with lags, to business cycle fluctuations in the U.S. in the period after the Global Financial Crisis. To do so, we employ two external instruments to identify the real economic activity shock in a partial shock approach.

Full paper available at: https://ssrn.com/abstract=2840730 This supplementary material to "Which Risk Factors Drive Oil Futures Price Curves?" includes the derivation of the futures price expression, details of the Kalman Filter utilised, and the equation for the sensitivity of the expected backwardation to parameter shocks. Results plots for other data periods, and descriptive statistics of the data are also presented. Furthermore, results for the HMF model and stepwise HMF model fits are given for other data periods. Finally, results for the beta and gamma Versions of the HMF model are detailed.

Full paper is available at: https://ssrn.com/abstract=3015582 Identifying firm connections by shared analyst coverage, we find that a connected-firm (CF) momentum factor generates a monthly alpha of 1.68% (t = 9.67). In spanning regressions, the alphas of industry, geographic, customer, customer/supplier industry, single- to multi-segment, and technology momentum factors are insignificant/negative after controlling for CF momentum. Similar results hold in cross-sectional regressions and in developed international markets. Sell-side analysts incorporate news about linked firms sluggishly. These effects are stronger for complex and indirect linkages. Consistent with limited investor attention, these results indicate that momentum spillover effects are a unified phenomenon that is captured by shared analyst coverage.

Full paper available at https://ssrn.com/abstract=3141041 We first present simulations investigating some properties of the Inverse Product Differentiation Logit (IPDL) model. Next, we provide a range of general methods for building Generalized Logit (GL) models along with illustrative examples that go beyond the IPDL model.

A comparison of "Governance and Taxes" with a previous working paper version reveals a number of irregularities that together suggest the analysis was not performed as described in the published version. In particular, the two versions claim to use different main empirical specifications, but the numbers in all 11 tables are exactly the same in both versions. An assessment of other comparisons between the two versions suggests that it is unlikely that these irregularities are unintentional errors. Instead, a straightforward explanation of these anomalies is data falsification: the working paper version accurately describes the main specification, and the published version misstates the main specification. I conclude by demonstrating that the main result, when accurately described, fails a simple placebo test and is therefore spurious.

In his Nobel speech, Eugene Fama claimed that critics have failed to offer a complete alternative to the efficient market hypothesis (EMH). More specifically, Fama stated, “Most important, the behavioral literature has not put forth a full blown model for prices and returns that can be tested and potentially rejected – the acid test for any model proposed as a replacement for another model.” Here I argue that Fama’s complaint is too strong. The EMH can fail and there still be no model that meets Fama’s criteria. This short paper explains why and offers a more reasonable alternative to the EMH based on the viewpoint that behavioral biases, though common, are state dependent.

The Chicago Board of Options Exchange (CBOE) advocates linking variable annuity (VA) fees to its trademark VIX index in a white paper (CBOE, 2013a, b). It claims that the VIX-linked fee structure has several advantages over the traditional fixed percentage fee structure. However, the evidence presented in the white paper was largely based on non-parametric extrapolation of historical data on market prices. Our work lays out a theoretical basis with a parametric model to analyze the impact of the VIX-linked fee structure and put to test some claims from the CBOE white paper. In a Heston-type stochastic volatility setting, we jointly model the dynamics of an equity index underlying VA policyholders’ accounts and the VIX index. In this framework, we price a guaranteed minimum maturity benefit (GMMB) with VIX-linked fees. Through numerical examples, we show that the VIX-linked fee reduces the sensitivity of the insurer’s liability to market volatility, when compared to a VA with the traditional fixed fee rate.

Studies about innovation find evidence of a positive relationship between technological advancement and firm performance, in particular when the innovative effort is continuous. This paper aims to further the analysis on the duration of R&D investment at the firm level. The contribution of this study is threefold: first, we extend M'a~nez et al. [2014], Triguero et al. [2014] analysis for Spain to the Italian case: we use a panel of manufacturing and service companies, thus enlarging the view of R&D duration within the European countries. Secondly, from a methodological point of view, we employ both discrete- and continuous-time duration models, in order to test the Proportional Hazards (PH) assumption, i.e. the assumption that the hazard rate is equivalent over time across groups. Last, but not least, we assess whether a firm?s likelihood of continuing investment in R&D depends on the market power of companies. We test alternative measures for market power: the classical price-cost margin and a new proxy for the firm demand elasticity, obtained from a specific survey question. Results are in line with the hypothesis that R&D presents considerable temporal spill overs and strong persistence, even once unobserved heterogeneity is controlled for. Also, we argue that the appropriate proxy for market power is the firm demand elasticity, and we find support for the Schumpeterian hypothesis.

The momentum premium is pervasive across international markets and different asset classes; however, the drivers of this premium are yet to be established. This paper contributes to the literature by examining the association between a leading economic indicator, namely return dispersion, and the momentum premium. This association is examined across four regional momentum strategies and a global momentum strategy. We document a strong association between return dispersion and the momentum premium using both ex-post and ex-ante empirical methods. This association is robust to the inclusion of a set of control variables and an alternate specification of return dispersion. We test a conditional momentum strategy that scales the unconditional momentum strategy by the level of return dispersion and find that the conditional momentum strategy outperforms the unconditional momentum strategy in all regions. The results presented in this paper document the dynamic association between risk and the momentum premium.

Random utility models are widely used to estimate preference parameters. In the case of intertemporal choice, the two most common models are the discounted logit and one we call the discounted Luce. Due to their apparent similarity, the choice to use one model or the other seems irrelevant. In this paper, we argue that the discounted Luce is superior to the discounted logit in two significant aspects. First, in relevant applications, the discounted Luce is monotone in the sense of Apesteguia and Ballester (2018), while the discounted logit is not. Second, we show that the discounted logit is incompatible with a property of choice probabilities we call “weak stationarity”. The latter is compatible with common assumptions on the random nature of choices and is often not falsifiable with commonly available data. Fitting a logit model to weakly stationary choice probabilities biases the time-preference estimates. On the contrary, the discounted Luce can be safely used when choice probabilities are weakly stationary. An application to an existing dataset supports the theoretical results.

The online Supplement presents the proof the auxiliary Lemmas 1-6, the entire set of tables with results from the Monte Carlo and the empirical studies, and further discussion on selected topics. Full paper is available at: https://ssrn.com/abstract=2707176

This Appendix contains details on several technical points and additional empirical results. Sections in this Appendix are indexed by letters and formulas/tables/figures by a letter followed by a number (e.g. A.1). Sections and formulas/tables/figures of the paper are referenced by numbers. In Section A, we expose the estimation procedure of the models employed in the paper. In Section B, we explain the approximation used to avoid the path dependence problem in Markov Switching models. In Section C, we provide the formulas of the marginal impact of volatility on correlations for each VDCC model. In Section D, we detail the estimation method and the results behind our findings about the long-run and short-run effects of the volatility on the correlations. In Section E, we report the application to the three stock data set (and other subsets of stocks) of the method explained in Section 4.1 to evaluate the performance of the constrained RSDC models. In Section F, we include and comment the estimates of the VDCC models for the thirty stock data set used in Section 4.2. Full paper is available at: https://ssrn.com/abstract=2965487

This codebook and the related dataset and statistical code accompanies Bernard Black, Antonio Gledson de Carvalho, Vikramaditya Khanna, Woochan Kim and B. Burcin Yurtoglu, Methods for Multicountry Studies of Corporate Governance: Evidence from the BRIKT Countries, 183 Journal of Econometrics 230-240 (2014), and explains the accompanying replication dataset and Stata code. There is a link to this codebook, dataset, and code from the working paper version of this article, at http://ssrn.com/abstract=2219525, and also from an “expanded working paper” version of this article, at http://ssrn.com/abstract=2359126. Comments on the dataset, the code, and this overview are welcome; please direct them to Prof. Black at bblack@northwestern.edu.

Mean-Variance portfolios are optimal in-sample, however they tend to perform poorly out-of-sample (even worse than the 1/N naive portfolio!) We introduce a new portfolio construction method that substantially improves the Out-Of-Sample performance of diversified portfolios.The full paper is available at: http://ssrn.com/abstract=2708678.

I. INTRODUCTION Scholarly articles are the coin of the realm in modern academia; they influence researchers' career paths, salaries, and reputations (Cole and Cole 1967; Ellison 2013; Gibson, Anderson, and Tressler 2014; Smith and Eysenck 2002), as well as their departments' and universities' rankings (Hazelkorn 2011; Zimmermann 2013). The question as to how to measure the impact or importance of an article is a topic of much debate (Meho 2007; Vucovich, Baker, and Smith 2008), but the appeal of having "unobtrusive measures that do not require the cooperation of a respondent and do not themselves contaminate the response (i.e., they are non-reactive)" (Smith 1981, 84) has made citation counts the de facto standard for measuring scholarly articles' impact. The origin of citation counts dates back to Gross and Gross's (1927) seminal paper (1); since then, the adoption of citation counts as a tool for measuring articles' importance has been overwhelming. Technological advances have had an effect on the popularity of this practice. As in many other fields, the availability and use of detailed data have grown exponentially since the onset of the "data revolution" (Einav and Levin 2014) and have been leveraged in recent years by automated citation indexing services such as Cite-Seer (Giles, Bollacker, and Lawrence 1998) and Google Scholar (see Giles 2005), which collect large amounts of citation data and make it accessible to the general public free of charge. Currently, citation counts are being used not only to measure the visibility, impact, and quality of articles but also to measure the performance of researchers, research laboratories, departments, academic journals and, to some extent, national science policies (e.g., Bayer and Folger 1966; Garfield 1972; King 2004; Narin 1976; Oppenheim 1995; Tijssen, Van Leeuwen, and Van Raan 2002). The influence that publishing has on the careers of scholars (especially young ones) is clearly reflected in the old mantra "publish or perish." (2) One could argue that the use of citation counts to evaluate scientific output has caused this phrase to fall short of the mark. Today, it is not just about publishing; it is about high impact-publishing (i.e., publications with substantial citation counts). Although the value of objectively quantifying the importance of academic papers is evident, a great deal of criticism has been made of the practice of naively using citation analysis to compare the impact of different scholarly articles without taking into account other factors which may affect citation patterns (see Bornmann and Daniel 2008). Among these criticisms, a recurrent one focuses on "field-dependent factors," which refers to the fact that citation practices vary from one area of science to another (with the focus generally being on differences in citation practices between hard science and the social sciences). In some fields, recent literature is cited more frequently than in others (see, e.g., Peters and Van Raan 1994), and different fields may have different structural characteristics which can increase or decrease the probability of a paper being cited. (3) If these arguments hold true, then they should be considered when the performance of researchers, journals, or institutions is being assessed. One good example of field-dependent factors' relevance is how they might affect different journals' impact factors. (4) If a given field tends to cite newer papers, journals that publish papers dealing with that field will clearly benefit in terms of their impact factors, and researchers who are encouraged to publish in high-impact journals will have an incentive to focus their studies on subjects in that field. What about economics? Economics as a discipline has not been exempt from these trends. Economic journals' impact factors and economic departments' rankings and tenure offerings are all influenced, to a greater or lesser degree, by the citation patterns of economic research articles (see, among others, Coupe 2003; Ellison 2013; Gibson, Anderson, and Tressler 2014; Hamermesh and Pfann 2012; Hamermesh, Johnson, and Weisbrod 1982; Hilmer, Hilmer, and Ransom 2012; Ruane and Tol 2008). …

In this paper, we propose a DSGE model with the term structure of interest rates drawing on the framework introduced by Andrés et al. (2004) and Marzo et al. (2008). In particular, we reproduce segmentation in financial markets by introducing bonds of different maturities and bond adjustment costs non-zero at the steady state, introducing a structural liquidity frictions among bonds with different maturities: agents are assumed to pay a cost whenever they trade bonds. As a result, the model is able to generate a non-zero demand for bonds of different maturities, which become imperfect substitutes, due to differential liquidity conditions. The main properties of the model are analysed through both simulation and estimation exercises. The importance of the results are twofold. On one hand, the calibrated model is able to replicate the stylized facts regarding the yield curve and the term premium in the US over the period 1987:3-2011:3, without compromising its ability to match macro dynamics. On the other hand, the estimation, besides providing an empirical support to the theoretical setting, highlights the potentialities of the model to analyze the term premium in a microfounded macro framework. The results match very closely the behavior of actual yields, reflecting the recent activity of the Fed on longer maturities bonds.

The paper documents elements of work on the dynamic stochastic general equilibrium (DSGE) SOEPL model that has been carried out in recent years at the National Bank of Poland. In 2009 a new version of the model was developed (called SOEPL−2009) which in 2010 is to support an econometric model and experts’ forecasts in mid-term forecasting of inflation and economic activity. The paper consists of three basic parts. The first part is introductory and briefly outlines the development of macroeconometric methods which brought about the creation of new-keynesian models specified within the dynamic stochastic general equilibrium approach. The remaining two parts of the paper report specification, estimation results and some properties of the SOEPL−2009 DSGE model.

Can the potential availability of unemployment insurance (UI) affect the behavior of employed workers and the duration of their employment spells? I apply a regression kink design (RKD) to address this question using linked employer-employee data from the Brazilian labor market. Exploiting the UI schedule, I find 1% higher potential benefit level increases job duration by around 0.3%. Such result is driven by the fact that higher UI decreases the probability of job quits, which are not covered by UI in Brazil. These estimates are robust to permutation tests and a number of falsification tests. I develop a simple model to assess the economic relevance of this finding. It shows that the positive effect on employment duration implies that the optimal benefit level is higher than otherwise. More importantly, the model delivers a simple welfare formula based on sufficient statistics which can be easily linked to the data. A simple calibration exercise shows that this elasticity impacts welfare with a similar magnitude to the well-known elasticity of unemployment duration to benefit level.

This Appendix contains additional empirical results with respect to the published article. In Section 1, the posterior results for the HDP parameters of the IHMS- ARMA models are presented for the U.S. GDP growth rate and inflation series. In Section 2, we report additional in-sample and forecasting results for the same series. In Section 3, some results for a different truncation choice of the number of regimes in the approximate model are reported. Full paper available at: https://ssrn.com/abstract=2965441

Central banks are increasingly communicating their economic outlook in an effort to manage the public and financial market participants’ expectations. We provide original causal evidence that the information communicated and the assumptions underlying a central bank’s projection can matter for expectation formation and aggregate stability. Using a between-subject design, we systematically vary the central bank’s projected forecasts in an experimental macroeconomy where subjects are incentivized to forecast the output gap and inflation. Without projections, subjects exhibit a wide range of heuristics, with the modal heuristic involving a significant backward-looking component. Ex-Ante Rational dual projections of the output gap and inflation significantly reduce the number of subjects’ using backward-looking heuristics and nudge expectations in the direction of the rational expectations equilibrium. Ex-Ante Rational interest rate projections are cognitively challenging to employ and have limited effects on the distribution of heuristics. Adaptive dual projections generate unintended inflation volatility by inducing boundedly-rational forecasters to employ the projection and model-consistent forecasters to utilize the projection as a proxy for aggregate expectations. All projections reduce output gap disagreement but increase inflation disagreement. Central bank credibility is significantly diminished when the central bank makes larger forecast errors when communicating a relatively more complex projection. Our findings suggest that inflation-targeting central banks should strategically ignore agents’ irrationalities when constructing their projections and communicate easy-to-process information. Electronic supplementary material The online version of this article (10.1007/s10683-020-09684-6) contains supplementary material, which is available to authorized users.

In this paper we derive analytic implicit form conditions for the qualitative analysis of government spending multipliers and the optimal level of government spending in presence of non-separability between private and public components of aggregate demand. Using the simplest neo-classical flexible price model with no capital accumulation, we show that Edgeworth dependence is not a suitable condition to automatically assess the signs of the consumption and income multipliers, for which a more complex analysis must be carried out. We propose a detailed investigation of the form and the characteristics of the involved utility functions, which are crucial to such evaluation. We also show that if Edgeworth complementarity is strong enough, a public spending stimulus can raise at the same time private consumption and real activity. In order to reconcile our general framework with existing literature, we discuss recent examples of non-separable functional forms from the standpoint of our results, and argue that their consistency relies on specific assumptions about steady- state points.

One version of the consumption-based asset pricing model implies a linear relation between expected returns and expected consumption growth. This paper provides evidence that the expected real term structure contains information that can be used to forecast consumption growth. The evidence is strongest for the 1970's and 1980's. The real term structure contains more information than two alternative measures: lagged consumption growth and lagged stock returns. Further, the real term structure appears to have slightly more forecasting power than the leading commercial econometric models. This is the working paper version of my 1988 Journal of Financial Economics article.

The average of periodic growth rates is a downwardly biased estimator of the rate of growth of a country. The higher the variance of the periodical growth rates, the higher the downward bias. The longer the business cycle, the higher the downward bias. In this short paper, we demonstrate these facts on a number of different levels, from intuitive to quite technical. We suggest that the variability of growth rates be taken into account whenever a long term forecast is prepared.

Amid controversies surrounding aid effectiveness, an increasing number of empirical studies find support for the idea that aid can spur growth and that the aid-growth relationship is nonlinear. Lensink and White propose a model to illustrate the possible existence of what has been labeled an "aid Laffer curve." This short paper highlights the model's weaknesses and suggests that the model does not fulfill the purpose of illustrating the possible existence of negative returns to aid.

This study revisits the sectoral shifts hypothesis for the US for the period 1948 to 2011. A quantile regression approach is employed in order to investigate the asymmetric nature of the relationship between sectoral employment and unemployment. Significant asymmetries emerge. Lilien’s dispersion index is significant only for relatively high levels of unemployment and becomes insignificant for low levels suggesting that reallocation effects unemployment only when the latter is relative high. More job reallocation is associated with higher unemployment.

Matched employer-employee (panel) data sets are gaining increasing importance in the analysis of labour markets. In collaboration with Statistics Austria we recently initiated the set up of a matched employer-employee panel data set for Austria, which covers the years 2002-2005. The aim of the paper is to introduce the data set to a broader audience. We first present the set up of the panel data, indicating in more detail the data sources and matching procedure underlying the matched employer-employee data set for Austria. In a second step we show descriptive statistics of the main variables included in our data set. These various statistics encompass three levels of analysis: the aggregate level (i.e. the entire sample), firm level and individual (employee) level.

The purpose of this short paper is to show that inflation “band” targeting can solve the “time inconsistency” problem that exists under inflation “point” targeting by setting a relevant target range.Moreover, we show that inflation band targeting has the following two advantages, besides allowing for supply-shock measurements.1) It can produce output beyond natural levels, by setting the inflation rate within a target range and creating unexpected inflation. 2) It can mitigate inflation bias and help achieve a socially desirable inflation rate.

A short paper on a method of incorporating growth into the price earnings ratio and calculating the growth implied in a price earnings ratio.

Online Appendix to "MULTIVARIATE VOLATILITY MODELING OF ELECTRICITY FUTURES". Full paper available at: https://ssrn.com/abstract=2965508

We propose a Markov-switching dynamic factor model to construct an index of global business cycle conditions, to perform short-term forecasts of world GDP quarterly growth in real time and to compute real-time business cycle probabilities. To overcome the real-time forecasting challenges, the model accounts for mixed frequencies, for asynchronous data publication and for leading indicators. Our pseudo real-time results show that this approach provides reliable and timely inferences of the world quarterly growth and of the world state of the business cycle on a monthly basis.

This short paper is a comment on "Testing for Nonlinear Structure and Chaos in Economic Time Series" by Catherine Kyrtsou and Apostolos Serletis. We summarize their main results and discuss some of their conclusions concerning the role of outliers and noisy chaos. In particular, we include some new simulations to investigate whether economic time series may be characterized by low dimensional noisy chaos.

The measurement of credit quality is at the heart of the models designed to assess the reserves and capital needed to support the risks of both individual credits and portfolios of credit instruments. A popular specification for credit rating transitions is the simple, time-homogeneous Markov model. While the Markov specification cannot really describe processes in the long run, it may be useful for adequately describing short-run changes in portfolio risk. In this specification, the entire stochastic process can be characterized in terms of estimated transition probabilities. However, the simple homogeneous Markovian transition framework is restrictive. We propose a test of the null hypotheses of time-homogeneity that can be performed on the sorts of data often reported. We apply the tests to 4 data sets, on commercial paper, sovereign debt, municipal bonds and SP sovereign debt also looks Markovian (perhaps due to a small sample size); municipals are well-modeled by the Markov specification for up to 5 years, but could probably benefit from frequent updating of the estimated transition matrix or from more sophisticated modeling, and S&P Corporate ratings are approximately Markov over 3 transitions but not 4.

This short paper discusses some econometric flaws in the way the conditional covariance matrix is estimated in a bivariate orthogonal GARCH model. The practical implications of these problems are illustrated in two empirical cases. Although this kind of model is usually employed with many more than two time series, some downturns of the bivariate version might apply also to the more general case.

In this short paper some computational aspects of dynamic programming (DP) applied to the real option problem of the dual fuel boiler in (Kulatilaka, 1993) are examined. A Gauss code has been written, and it is reported in the text, for both pedagogical and practical purposes. As a matter of fact, understanding how the code works helps to delve better into the mechanics of the DP algorithm. On the other hand, the reported code is an "hands on" tool for those who want to apply the (Kulatilaka, 1993) model to real business situations. Since the estimation of the stochastic process driving the state variable of the system is crucial for a good application of the model, four different econometric methods have been applied to the estimation of Ornstein - Uhlenbeck parameters, namely OLS for the (Kulatilaka, 1993) and the (Dixit, Pindyck 1994) specifications, GMM and MLLE for (Roncalli, 1999) approach. Several comparative statics exercises have been performed on real data on oil, coal, natural gas and the boiler characteristics.