The probability conflation: A reply to Tetlock et al.

We respond to Tetlock et al. (2022) showing (1) how expert judgment fails to reflect tail risk and (2) the lack of compatibility between forecasting tournaments and tail-risk assessment methods (such as extreme value theory). More importantly, we communicate a new result showing a greater gap between the properties of tail expectation and those of the corresponding probability.     

An optional scrambled randomized response technique for practical surveys

Eichhorn and Hayre (J Stat Plan Inference 7:307–316, 1983) introduced the scrambled response technique to gather information on sensitive quantitative variables. Singh and Joarder (Metron 15:151–157, 1997), Gupta et al. (J Stat Plan Inference 100:239–247, 2002) and Bar-Lev et al. (Metrika 60:255–260, 2004) permitted the respondents either to report their true values on the sensitive quantitative variable or the scrambled response and developed the optional randomized response (ORR) technique based on simple random sample with replacement (SRSWR). While developing the ORR procedure, these authors made the assumption that the probability of disclosing the true response or the randomized response (RR) is the same for all the individuals in a population. This is not a very realistic assumption as in practical survey situations the probability of reporting the true value or the RR generally varies from unit to unit. Moreover, if one generalizes the ORR method as developed by these authors relaxing the ‘constant probability’ assumption, the variance of an unbiased estimator for the population total or mean can not be estimated as this involves the unknown parameter, ‘the probability of revealing the true response’. Here we propose a modified ORR procedure for stratified unequal probability sampling after relaxing the assumption of ‘constant probability’ of providing the true response. It is also demonstrated with a numerical exercise that our procedure produces better estimator for a population total than that provided by the method suggested by the earlier authors.     

The US debt–growth nexus along the business cycle

We use the US data gathered by Reinhart and Rogoff (2010) to assess whether debt affects economic growth differently at different phases of the business cycle. In order to do that, we extend the threshold regression model of Chudik et al. (2017) and propose a new threshold quantile ARDL regression model. Our results show that to stimulate growth policy makers can manage the debt/GDP percentage according to how well the economy is doing. The estimated quantile thresholds (range 31–53 per cent) are larger than the one found by Lee et al. (2017) using median regressions, but still (much) smaller than the 90 per cent of Reinhart and Rogoff. In particular, when the US economy observes growth rates above their median value, that is when a smaller debt-to-GDP threshold affects the performance of the economy. In a steady-state situation, in general, regardless of the position of the business cycle and whether the debt-to-GDP ratio is below or above its threshold effect, less debt as a percentage of GDP boosts the US growth. Remarkably, this effect was always greater before than after World War II. Moreover, the most recent decades have witnessed the negative (positive) effect of more (less) debt when the economy had growth rates at their first quartile (median and third quartile). That is, the US policy makers are advised to reduce the debt-to-GDP ratio during expansions to promote growth.     

A new method for measuring congestion in data envelopment analysis

In data envelopment analysis (DEA), there are two principal methods for identifying and measuring congestion: Those of Färe et al. [Färe R, Grosskopf S. When can slacks be used to identify congestion. An answer to W. W. Cooper, L. Seiford, J. Zhu. Socio-Economic Planning Sciences 2001;35:1–10] and Cooper et al. [Cooper WW, Deng H, Huang ZM, Li SX. A one-model approach to congestion in data envelopment analysis. Socio-Economic Planning Sciences 2002;36:231–8]. In the present paper, we focus on the latter work in proposing a new method that requires considerably less computation. Then, by proving a selected theorem, we show that our proposed methodology is indeed equivalent to that of Cooper et al.     

Quantile-based nonparametric inference for first-price auctions

We propose a quantile-based nonparametric approach to inference on the probability density function (PDF) of the private values in first-price sealed-bid auctions with independent private values. Our method of inference is based on a fully nonparametric kernel-based estimator of the quantiles and PDF of observable bids. Our estimator attains the optimal rate of Guerre et al. (2000), and is also asymptotically normal with an appropriate choice of the bandwidth.     

Identification-commitment inventory (ICI model): confirmatory factor analysis and construct validity

The aim of this study is to confirm the factorial structure of the Identification-Commitment Inventory (ICI) developed within the frame of the Human System Audit (HSA) (Quijano et al. in Revist Psicol Soc Apl 10(2):27–61, 2000; Pap Psicól Revist Col Of Psicó 29:92–106, 2008). Commitment and identification are understood by the HSA at an individual level as part of the quality of human processes and resources in an organization; and therefore as antecedents of important organizational outcomes, such as personnel turnover intentions, organizational citizenship behavior, etc. (Meyer et al. in J Org Behav 27:665–683, 2006). The theoretical integrative model which underlies ICI Quijano et al. (2000) was tested in a sample (N = 625) of workers in a Spanish public hospital. Confirmatory factor analysis through structural equation modeling was performed. Elliptical least square solution was chosen as estimator procedure on account of non-normal distribution of the variables. The results confirm the goodness of fit of an integrative model, which underlies the relation between Commitment and Identification, although each one is operatively different.     

On the computation of optimal monotone mean–variance portfolios via truncated quadratic utility

We report a surprising link between optimal portfolios generated by a special type of variational preferences called divergence preferences (see Maccheroni et al., 2006) and optimal portfolios generated by classical expected utility. As a special case, we connect optimization of truncated quadratic utility (see ?erný, 2003) to the optimal monotone mean–variance portfolios (see Maccheroni et al., 2009), thus simplifying the computation of the latter.     

On possibilities and limitations of using self-anchoring scales in web surveys

Self-anchoring scales were first mentioned by Kilpatrick and Cantril (J Indiv Psychol 16:158–170, 1960) and Cantril (The pattern of human concerns, 1965) as rating instruments in which the end anchors are defined by the respondent himself, basing on his own assumptions, perceptions, goals and values. The uses of these scales are legion and they have shown to be very useful in reducing measurement bias in cross-cultural research (Cantril, The pattern of human concerns, 1965; Bernheim et al. J. Happiness Stud. 7:227–250, 2006). The first part of the current study investigates whether context effects can be lessened or eliminated by using self-anchoring scales. For this purpose, an experiment similar to the ones by Couper et al. (Public Opin Q 71:623–634, 2004, Public Opin Q 68:255–266, 2007), in which they manipulated images that figured in a web survey, was conducted. The hypothesis that self-anchoring scales can reduce contextual bias, is not supported by our data. The second part of the study investigates if and how self-anchoring scales affect drop-out during the filling-out of questionnaires. It is found that, compared to a regular rating scale, a larger proportion of respondents drop-out. Moreover, subjective preferences for the one or the other scale do not seem to differ.     

Analysis of information feedback and selfconfirming equilibrium

Recent research emphasizes the importance of information feedback in situations of recurrent decisions and strategic interaction, showing how it affects the uncertainty that underlies selfconfirming equilibrium (e.g., Battigalli et al., 2015, Fudenberg and Kamada, 2015). Here, we discuss in detail several properties of this key feature of recurrent interaction and derive relationships. This allows us to elucidate different notions of selfconfirming equilibrium, showing how they are related to each other given the properties of information feedback. In particular, we focus on Maxmin selfconfirming equilibrium, which assumes extreme ambiguity aversion, and we compare it with the partially-specified-probabilities (PSP) equilibrium of Lehrer (2012). Assuming that players can implement any randomization, symmetric Maxmin selfconfirming equilibrium exists under either “observable payoffs,” or “separable feedback.” The latter assumption makes this equilibrium concept essentially equivalent to PSP-equilibrium. If observability of payoffs holds as well, then these equilibrium concepts collapse to mixed Nash equilibrium.     

A two-step estimator for large approximate dynamic factor models based on Kalman filtering

This paper shows consistency of a two-step estimation of the factors in a dynamic approximate factor model when the panel of time series is large (n large). In the first step, the parameters of the model are estimated from an OLS on principal components. In the second step, the factors are estimated via the Kalman smoother. The analysis develops the theory for the estimator considered in Giannone et al. (2004) and Giannone et al. (2008) and for the many empirical papers using this framework for nowcasting.     

Congestion in the Chinese automobile and textile industries revisited

This paper re-examines a problem of congested inputs in the Chinese automobile and textile industries, which was identified by Cooper et al. [Cooper WW, Deng H, Gu B, Li S, Thrall RM. Using DEA to improve the management of congestion in Chinese industries (1981-1997). Socio-Economic Planning Sciences 2001;35:227-242]. Since these authors employed a single approach in measuring congestion, it is worth exploring whether alternative procedures would yield very different outcomes. Indeed, the measurement of congestion is an area where there has been much theoretical debate but relatively little empirical work. After examining the theoretical properties of the two main approaches currently available, those of Färe et al. [Färe R, Grosskopf S, Lovell CAK. The measurement of efficiency of production. Boston: Kluwer-Nijhoff; 1985] and Cooper et al., we use the data set assembled by Cooper et al. for the period 1981-1997 to compare and contrast the measurements of congestion generated by these alternative approaches. We find that the results are strikingly different, especially in terms of the amount of congestion identified. Finally, we discuss the new approach to measuring congestion proposed by Tone and Sahoo [Tone K, Sahoo BK. Degree of scale economies and congestion: a unified DEA approach. European Journal of Operational Research 2004;158:755-772].     

Reinforced urn processes for credit risk models

We propose a Bayesian nonparametric model to estimate rating migration matrices and default probabilities using the reinforced urn processes (RUP) introduced in Muliere et al. (2000). The estimated default probability becomes our prior information in a parametric model for the prediction of the number of bankruptcies, with the only assumption of exchangeability within rating classes. The Polya urn construction of the transition matrix justifies a Beta distributed de Finetti measure. Dependence among the processes is introduced through the dependence among the default probabilities, with the Bivariate Beta Distribution proposed in Olkin and Liu (2003) and its multivariate generalization.     

Internal habits formation and optimality

In a very influential model with internal habits, Carroll et al., (2017, 2000), establish that an increase in economic growth may cause a positive change in savings. The optimality of this result, and of many other contributions using a similar framework, has been questioned by some authors who have observed that the parametrization used in these models always implies a utility function not jointly concave in consumption and habits. In this paper, we revisit the optimality issue and, using advanced techniques in Dynamic Programming, we answer the following long-standing open questions: (i) Is the solution found in Carroll et al., (2017, 2000) optimal? (ii) Is it also unique or do other optimal solutions exist?     

On fitting the conditional difference asymmetry models to square contingency tables with nominal categories

In this paper, we implement the conditional difference asymmetry model (CDAS) for square tables with nominal categories proposed by Tomizawa et al. (J. Appl. Stat. 31(3): 271–277, 2004) with the use of the non-standard log-linear model formulation approach. The implementation is carried out by refitting the model in the 3 ×  3 table in (Tomizawa et al. J. Appl. Stat. 31(3): 271–277, 2004). We extend this approach to a larger 4 ×  4 table of religious affiliation. We further calculated the measure of asymmetry along with its asymptotic standard error and confidence bounds. The procedure is implemted with SAS PROC GENMOD but can also be implemented in SPSS by following the discussion in (Lawal, J. Appl. Stat. 31(3): 279–303, 2004; Lawal, Qual. Quant. 38(3): 259–289, 2004).     

Cross-sectional dependence robust block bootstrap panel unit root tests

In this paper we consider the issue of unit root testing in cross-sectionally dependent panels. We consider panels that may be characterized by various forms of cross-sectional dependence including (but not exclusive to) the popular common factor framework. We consider block bootstrap versions of the group-mean (Im et al., 2003) and the pooled (Levin et al., 2002) unit root coefficient DF tests for panel data, originally proposed for a setting of no cross-sectional dependence beyond a common time effect. The tests, suited for testing for unit roots in the observed data, can be easily implemented as no specification or estimation of the dependence structure is required. Asymptotic properties of the tests are derived for T going to infinity and N finite. Asymptotic validity of the bootstrap tests is established in very general settings, including the presence of common factors and cointegration across units. Properties under the alternative hypothesis are also considered. In a Monte Carlo simulation, the bootstrap tests are found to have rejection frequencies that are much closer to nominal size than the rejection frequencies for the corresponding asymptotic tests. The power properties of the bootstrap tests appear to be similar to those of the asymptotic tests.     

Testing for jumps in noisy high frequency data

This paper proposes a robustification of the test statistic of Aït-Sahalia and Jacod (2009b) for the presence of market microstructure noise in high frequency data, based on the pre-averaging method of Jacod et al. (2010). We show that the robustified statistic restores the test’s discriminating power between jumps and no jumps despite the presence of market microstructure noise in the data.     

Land-price dynamics and macroeconomic fluctuations with nonseparable preferences

In this paper, we introduce a complementary relationship between consumption and labor hours by revising the household’s period utility function in Liu et al. (2013). The revision concomitantly allows for a finite Frisch elasticity of labor supply and a stronger consumption smoothing motive. We find that, in general, the estimation of Liu et al. (2013) is quite robust. In addition, the propagation mechanism of the credit constraint triggered by a housing demand shock still persists. However, the amplification effect of the credit constraint triggered by the housing demand shock on key macroeconomic variables is greatly muted. We also find that, except for land price fluctuations, the housing demand shock cannot act as the primary force to drive the fluctuations in other macroeconomic variables.     

Jump dynamics,spillover effect and option valuation

In this paper, we propose an affine discrete-time model that incorporates the jump process and spillover effect for valuing the 50 ETF options in China. Based on the proposed model, a closed-form solution is also derived for the new dynamics of underlying asset, which facilitates option pricing. The empirical results show that the proposed model offers greater economic benefit with reduced pricing errors than the traditional benchmark models, including the popular HNGARCH model of Heston and Nandi (2000), GARV model of Christoffersen et al. (2014), and BPJVM model of Christoffersen et al. (2015). Our finding is important for financial risk management and investment in Chinese derivatives market.     

Reexamination on updating Choquet beliefs

Eichberger et al. (2007)  characterize the full Bayesian update rule for capacities. This paper shows that a conditional preference relation represented by the Choquet expected utility with respect to the updated capacity through the rule does not satisfy the axiom of Conditional Certainty Equivalence Consistency. A counterexample is provided and it is proved that a relaxation of the axiom maintains their results.