Impact of COVID-19 on the US and Texas Economy: A General Equilibrium Approach

This paper examines the impact of COVID-19 on the US and Texas economy using a computable general equilibrium model, REMI PI+. We consider three scenarios based on economic forecasts from various sources, including the University of Michigan’s RSQE (Research Seminar in Quantitative Economics), IMF, and the Wi orld Bank. We report a GDP loss of $106 million (a 6% decline) with 1.2 million jobs lost (6.6%) in Texas in 2020. At the national level, GDP loss is $996 billion (a 5% decline) with 11.5 million jobs lost (5.5%) in the same year. By 2026, the aggregate total GDP loss in Texas ranges from $378 to $629 million. The estimated unemployment rate in Texas in 2021 ranges from 5% to 7.7%, depending on modeling assumptions. The granularity of the CGE results allow examination of the most and least impacted industries. Health Care and Social Assistance, Construction, and Accommodation and Food Services incur the most job loss while State and Local Government and Farm will likely see an increase in jobs for 2020. These insights separate our work from most current impact studies.

Self-Concept Transformation on Senior Secondary School Students' Academic Achievement in Central Zone, Plateau State, Nigeria

Economics is one of the popular subjects in the Senior Secondary School (SSS) curriculum, and it covers the fundamental aspects of human lives concerning scarcity of resources. Proper understanding of the basic concept will enable students to realize the benefit of the subject. This study examined the effects of the self-concept transformation package on senior secondary school student's academic achievement in the quantitative aspect of Economics in Central Zone, Plateau State, Nigeria. A quasi-experimental research design, the non-equivalent control- group design, was used for this study. The sample size consisted of 105 economics SS2 students from intact classes of the four sampled schools. There were 50 and 55 students in the experimental and control group, respectively. Multi-Stage Cluster sampling techniques were used for this study. The instruments used for data collection were the Multi-dimensional Self-Concept Scales (MSS) and Quantitative Economics Achievement Test (QEAT). Research questions were analyzed using descriptive statistics, while the t-test of independent sample and Analysis of Covariance (ANCOVA) was used to test the hypotheses. The statistical package for social sciences (SPSS) version 23 was used for the analysis. The results show that the self-concept transformation package positively and significantly affected students' self-concept and academic achievement in quantitative economics. The study recommended that the use of abusive words on students by Parents and guardians should be discouraged to strengthening their student's self-concept.

segregsmall: A command to estimate segregation in the presence of small units

Suppose that a population, composed of a minority and a majority group, is allocated into units, which can be neighborhoods, firms, classrooms, etc. Qualitatively, there is some segregation whenever allocation leads to the concentration of minority individuals in some units more than in others. Quantitative measures of segregation have struggled with the small-unit bias. When units contain few individuals, indices based on the minority shares in units are upward biased. For instance, they would point to a positive amount of segregation even when allocation is strictly random. The command segregsmall implements three recent methods correcting for such bias: the nonparametric, partial identification approach of D’Haultfœuille and Rathelot (2017, Quantitative Economics 8: 39–73); the parametric model of Rathelot (2012, Journal of Business & Economic Statistics 30: 546–553); and the linear correction of Carrington and Troske (1997, Journal of Business & Economic Statistics 15: 402–409). The package also allows for conditional analyses, namely, measures of segregation accounting for characteristics of the individuals or the units.