Unrelated Regression System Research Articles

Impact of Covid-19 on leisure consumption in the US

ABSTRACT The COVID-19 pandemic has changed the way time is allocated towards market and non-market activities. This paper looks at the effect of the pandemic on a key category of non-market activity – leisure. We use micro-data from the American Time Use Survey to see how the pandemic affected leisure in the United States. A seemingly unrelated regression system is deployed to examine how the pandemic affects various leisure activities such as television viewing, socialising, reading/writing, active sports, games, and computer use. Apart from socialising, which was actively discouraged during the pandemic, all major leisure activities saw an increase, which resulted in overall leisure going up in the Covid year 2020 by 5%, compared to 2019. However, the impact is statistically significantly different for different types of leisure activities. Active leisure is being consumed less while passive leisure is being consumed more – pointing towards an increased sedentarization of lifestyles. Since previous studies have shown passive leisure to be negatively associated with health, our result has important implications for the health and well-being of Americans, and if the trend continues, policymakers should actively incentivise the consumption of active forms of leisure.

Associations of Physical Activity Enjoyment and Physical Education Enjoyment With Segmented Daily Physical Activity in Children: Exploring Tenets of the Trans-Contextual Model of Motivation

Purpose: This study examined the associations between physical activity enjoyment and physical education enjoyment with segmented physical activity in children. Method: Using student-level data from the School Wellness Integration Targeting Child Health project (N = 1,986), the Youth Activity Profile (YAP) assessed physical activity before school, during physical education, recess, after school, and evening. Segmented YAP scores were regressed onto two enjoyment variables using a seemingly unrelated regression system. Results: Physical activity enjoyment and physical education enjoyment significantly associated with YAP scores during all segments, but physical education enjoyment showed stronger associations during physical education. Older students had higher physical activity before school and in the evening, and physical education enjoyment was more influential for females before school. Conclusion: This study supports tenets of the trans-contextual model of motivation. Improving both physical activity and physical education enjoyment may yield improvements in physical activity behaviors during physical education and all other day segments.

A Markowitz‐based alternative model: Hedging market shocks under endowment constraints*

AbstractThis paper suggests an alternative method of investing funds managed by endowments and foundations that is largely based on the work of Harry Markowitz, Arnold Zellner, and Nassim Taleb. Recognizing most endowments work around their traditional allocation of capital to bonds and stocks, this paper offers another piece of evidence that alternative methods of protection may be advantageous when their portfolios are constructed with forecasting error in mind. It suggests taking long only positions in two Markowitz optimized long/short funds. This could allow exposure to short positions while under long only constraints, and if done correctly, outperform the typical stock/bond split, providing the needed premium for payout liabilities. While this is frequently done by endowments, these funds typically invest in portfolios that are poorly constructed. The approach discussed in this paper utilizes the covariance of forecasting errors in optimizing each of the before mentioned portfolios; they would also be constructed for performance during normal market conditions and unpredictable Black Swan event. This optimization method can be achieved by using a seemingly unrelated regression system for forecasted returns, thereby providing the theoretically correct variance covariance to be utilized in optimization. Even with the very simplistic forecasting model utilized, application of the correct methodology provides enhanced performance. The result is a portfolio that maintains its value during adverse market conditions without sacrificing annual return. The risk‐adjusted return of a portfolio constructed using the methodology outlined in this paper would be far higher than that of the stock/bond approach foundations and endowments have relied upon, even during a period of extremely good bond performance, by historical standards.

Chief executive officer compensation, firm performance, and strategic coopetition: A seemingly unrelated regression approach

Coopetition denotes the simultaneous cooperation and competition in a business relationship and is broader in depth and width than competition. This pioneering comparative study employs a seemingly unrelated regression system to investigate the impact of peer‐pay bias and pay‐for‐relative performance upon the highly controversial chief executive officer (CEO) pay. The analysis of the 21 Dow–Jones firms from 1992 to 2013 shows that the pay‐for‐performance relationship is contingent on the fit between CEO's strategic decisions and firm's core competency. The CEO pay is driven by the intensification of firm coopetition. We contribute to executive compensation, corporate strategy, and econometric methods.

CO2 emissions and human development in OECD countries: granger causality analysis with a panel data approach

Carbon dioxide (CO2) is a major greenhouse gas emitted through human activities resulting from energy use. This study examines the causal relation between the logarithms of the human development index and CO2 emissions in 33 Organization for Economic Co-operation and Development countries for 1992–2011. Moreover, it applies a new panel data approach developed by Konya (2006). This approach is based on the seemingly unrelated regression system and Wald tests with country-specific bootstrap critical values. The results obtained from the Granger causality analysis support the growth hypothesis for Denmark, Ireland, Israel, Italy, Japan, Korea, Luxembourg, Poland, Spain, Slovakia, Turkey, and the U.S. In addition, they support the conservation hypothesis for Chile, Czech Republic, Estonia, Finland, France, Greece, New Zealand, and Mexico. The feedback hypothesis is observed for Iceland, Norway, Portugal, and Switzerland as well as the neutrality hypothesis of the other countries (Australia, Austria, Belgium, Canada, Hungary, Netherlands, Slovenia, Sweden, and the UK). This implies that conservation policies that are related to coal, gas, electricity, and oil consumption can reduce CO2 emissions but may simultaneously hinder economic growth and human living standards. However, if conservation policies are not implemented, the detrimental effects of environmental degradation could also affect human living standards. Therefore, policymakers must develop strategic plans to reduce carbon emissions that do not negatively impact their constituents. One possible way to achieve this is by increasing the efficiency of energy use.

On estimating regression coefficients in seemingly unrelated regression system

In the system of m (m ≥ 2) seemingly unrelated regressions, we show that the Gauss-Markov estimator (GME) of any regression coefficients has unique simplified form, which exactly equals to the one-step covariance-adjusted estimator of the regression coefficients, and hence we conclude that for any finite k ≥ 2 the k-step covariance-adjusted estimator degenerates to the one-step covariance-adjusted estimator and the corresponding two-stage Aitken estimator has exactly one simplified form. Also, the unique simplified expression of the GME is just the estimator presented in the Theorem 1 of Wang’ work [1988]. A new estimate of regression coefficients in seemingly unrelated regression system, Science in China, Series A 10, 1033-1040].

Improved Liu-Type Estimator of Parameters in Two Seemingly Unrelated Regressions

We consider the parameter estimation in two seemingly unrelated regression systems. To overcome the multicollinearity, we propose a Liu-type estimator in seemingly unrelated regression systems. The superiority of the new estimator over the classic estimator in the mean square error is discussed and we also discuss the admissibility of the Liu-type estimator.

Transportation Infrastructure Performance Modeling through Seemingly Unrelated Regression Systems

Deterioration modeling plays a central role in performance prediction, a key component in transportation infrastructure system management. The deterioration of a facility can be expressed in terms of numerous indicators. For instance, in the case of highway pavements, these indicators range from panel ratings (such as pavement serviceability rating) to distress variables (such as percentage of surface cracking and rut depth). Different indicators capture different deterioration mechanisms; however, they may be correlated to each other. Numerous studies have been conducted involving modeling the deterioration of transportation facilities. Empirical regression has proved to be an effective way to characterize the relationship between the explanatory variables and dependent variable (performance indicator). The majority of these models were established with the focus on each individual performance indicator separately and independently. However, one type of indicator does not sufficiently capture the performance of a facility. For instance, while a softer binder may improve fatigue cracking performance, it could possibly be detrimental to rutting performance. As a result, the facility deterioration mechanism may not be fully characterized by single models. Since decision making in infrastructure management usually relies on a series of different performance indicators, the systematic considerations of these indicators is imperative. In this study, a flexible and statistically sound modeling approach is presented to jointly account for the performance of a transportation facility based on two indicators. A system of nonlinear structured econometric models is established to capture different deterioration processes in terms of these indicators. Due to the fact that the selected indicators represent the performance of a single section from different aspects, the correlation among the models in the system is particularly addressed. A case study is presented to demonstrate the feasibility of the proposed methodology with focus on in-service highway pavements. Two major indicators, international roughness index and rut depth, widely used in characterizing flexible pavement performance, are adopted and analyzed in the model system. The results demonstrate that: (1) different indicators are associated with different deterioration mechanisms reflected through their respective parameters; (2) the correlation of different deterioration mechanisms and relation of parameters across the models can be captured through relevant statistics; and (3) model estimation is efficient when accounting for the correlation among the models.

An Empirical Evaluation of Long Term Advisors and Short Term Interventions in Technical Assistance and Capacity Building

Technical assistance to improve the capacity of regulatory agencies around the world remains a key priority for international aid efforts. Technical assistance is critical to younger antitrust agencies because more effective agencies can protect consumers against anti-competitive conduct. Beginning in the 1990s, the rapid adoption of antitrust laws and development of agencies to interpret and enforce these laws has transformed the competitive landscape in many countries. Indeed, more than half of the countries with an antitrust legal framework enacted antitrust laws in the past 15 years. Many of the newer antitrust agencies are not as effective as they need to be to improve the well being of consumers and protect against anti-competitive conduct. Consequently, donors have assigned a significant amount of time and financial resources to technical assistance to raise the capacity and effectiveness of these younger agencies. However, quantitative analysis of the impact of this technical assistance remains limited at best. In a previous paper, we undertook a general analysis of antitrust technical assistance. In this paper we focus on what appears to be a particularly important part of technical assistance and capacity building - the use of long term advisors (LTA) and short term interventions (STI). In 2005, the International Competition Network conducted a survey of antitrust agencies that received LTA and STI services from a wide array of donor agencies. We first perform a descriptive assessment of the survey data. We find LTAs to be more effective than STIs in preparing the agency for tackling work they could not have undertaken previously and in confronting cartels. Most LTA and STI services arrived directly from developed world antitrust agencies and lawyers were superior to economists for STI work while economists tend to perform best as LTAs. In a more general empirical framework, we model the effectiveness of LTA and STI interventions using key survey questions about the initial preparation phase, the ability of the interventions to improve internal tactical qualities of the agency, and the ability of the interventions to improve the agency in its strategic mission. We estimate a three equation seemingly unrelated regression system designed to tease out the factors that led to a successful preparation of tactical and strategic technical assistance. The most important findings are related to two structural features of recipient antitrust agencies. Our most prominent finding is that recipient agencies absorb LTA and STI services best when the agency head has a rank of minister or higher and/or when agencies had prosecutorial discretion. At the heart of these agency features is the relative power position of the agency in the domestic political and economic structure. Those agencies with a strong power base seem well positioned to receive the current formatted technical assistance involving LTAs and STIs. Donors should focus on modifying the technical assistance to agencies with less power and should push for stronger agency autonomy and authority. A second prominent finding was that bilateral donor relationships did remarkably better in helping the agencies with their strategic mission. Perhaps bilateral LTA and STI perform better because of a better understanding of the political and economic realities these agencies face or because these donors provide aid through developed world competition agencies. Our suggestion is that multilateral donor agencies work hard to overcome deficiencies that their organizational structure presents to recipient agencies. Overall, our analysis of technical assistance efforts in one field of complex regulation (antitrust) may prove relevant to policies of how to make assistance more effective across regulatory fields.

ITERATIVE QUASI-LIKELIHOOD FOR SEEMINGLY UNRELATED REGRESSION SYSTEMS

In the seemingly unrelated regression systems, the existing quasi-likelihood is always involved in the difficult problem of calculating inverse of a high order matrix specially for large systems. To avoid this problem, the new quasi-likelihood proposed in this paper is based mainly on a linearly iterative process of some unbiased estimating functions. Some finite sample properties and asymptotic behaviours for this new quasi-likelihood are investigated. These results show that the new quasi-likelihood for parameter of interest is E-sufficient, iteratively efficient and approximately efficient. Some examples are given to illustrate the theoretical results.

Financial risk analysis of three aeration regimes in catfish cage culture

This study analysed the benefits and costs of three airlift aeration regimes — continuous (24 hr), partial (9 hr/night plus emergencies), and no aeration — for channel catfish in cages. Data from four field studies included four dependent variables based on size at harvest, and six independent variables. Four regression models were fit with a modified Cobb‐Douglas production function in a Seemingly Unrelated Regression system. Yield projections from the production function were then used in a stochastic economic model with prices and variable costs expressed as triangular distributions. Results indicated that none of the aeration methods was preferred to the others by either first‐ or second‐degree stochastic dominance criteria, although partial aeration was the risk‐neutral choice. A power analysis was used to demonstrate that an impractical number of replicates would be needed to detect a difference between partial and continuous aeration that was both economically and statistically significant.

Existence of the uniformly minimum risk unbiased estimator in seemingly unrelated regression system

For a seemingly unrelated regression system with the assumption of normality, a necessary and sufficient condition for the existence of the Uniformly Minimum Risk Unbiased (UMRU) estimator of regression coefficients under strictly convex loss is obtained; it is proved that any unbiased estimator can not improve the least squares estimator; it is also shown that no UMRU estimator exists under missing observations.

The efficiency of least squares estimators of a seemingly unrelated regression model

A measure defined by Bloomfield and Watson (1975)is applied to measure the relative performance between the ordinary least squares estmates (OLES) and Gauss-Markov estimates for a two-equation model of a seemingly unrelated regression system. Results obtained are compared with those obtained by Zellner (1963), Ravankar (1974) and Chang and Lin (1984). It can be seen that this efficeiency depends only the correlation coefficient of disturbances between two regression equations and is independent of the sample size.

Hierarchical interaction: The modeling of a competing central place system

This paper presents a comparative analysis of alternative specifications of the competing destinations model. The competing central place extension is shown to be a model that is sensitive to the spatial and structural intricacies of hierarchical interaction. It is stressed that choice of estimation procedure is as important as model specification, where significance of extracted parameter estimates are subject to spatial autocorrelative transformations. An interactional simulation exercise is performed to expose conceptual and methodological differences in parameter estimates using ordinary least squares (OLS), estimated generalized least squares (EGLS), seemingly unrelated group regression (SUR), and a spatially adjusted version of the seemingly unrelated regression system (SASUR). The combination of a competing central place or weighted destinations model and SASUR is shown to exhibit some interesting results in the estimation of a simulated flow pattern. The competing central place variation of the competing destinations model is proposed as a generalization which recognizes the hierarchical components of flow patterns.

A note on the estimation of seemingly unrelated regression systems

In a system of simultaneous equations, one obtains the same results for the overidentified equations by applying three-stage least squares to those equations alone as one would obtain by applying three-stage least squares to the entire system. This paper obtains an analogous result for a system of seemingly unrelated regressions. In doing so it generalizes earlier results of several other authors.

A Program for Econometric and Spectral Analysis-EAS

and FORTRAN IV which is designed to accommodate most researchers' everyday econometric needs. However, this program is particularly useful when spectral methods are combined (in an ex post sense) with regression and simultaneous equations estimation., Residuals from regression or simultaneous equations estimation are easily saved by EAS and used in later spectral computations by using only two program statements.1 All spectral computations are highly efficient since the fast Fourier transform techniques developed by Cooley and Tukey [2] are used throughout. The program also allows algebraic expressions to be used directly in regression statements to define dependent or independent variables. Hence, special regression equations like the harmonic analysis model can be easily estimated with a single program statement. A partial enumeration of the program's capabilities is as follows: ordinary and weighted least squares regression; multivariate regression and estimation of Zellner's seemingly unrelated regression system; structural estimation of simultaneous equations by two-stage least squares, three-stage least squares, limited information maximum likelihood, k-class, double k-class, h-class, and Nagar's minimum bias k-class methods; power spectrum analysis, cross spectrum analysis, and simple frequency domain regression; random number generation and Monte Carlo methods; principal components analysis; estimation of partially nonlinear models by likelihood search techniques; and estimation of certain distributed lag models by Dhrymes' [3] methods. The program accommodates problems in which the sample size and number of yariables do not exceed 32,767 and 1,823, respectively, but the dynamic core allocation features of PL/1 are used to economize on all smaller problems. The design of the program is especially useful when a large data bank (subject to the abQve limitations) is to be maintained, updated, and periodically accessed for various types of econometric analyses. Most small- to medium-sized