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Abstract: Private tutoring is widely used by parents to enhance their children’s academic performance. However, its effectiveness depends on both the quality of instruction and students’ study effort, which parents cannot directly control. Excessive workload may also lead to depressive symptoms, reducing learning efficiency. This paper focuses on two questions: (1) Is tutoring an efficient educational investment ; (2) How do depressive symptoms influence its efficiency. I develop a two-period dynamic structural model with two sequential decision makers—parents and children. Parents choose tutoring expenditure based on grades, expected human capital, and their preferences; children choose study effort considering mental health and perceived returns to effort. Using CFPS data on high school students, This paper jointly estimates educational investment and effort, incorporating the interaction between mental health and study effort.

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Abstract: Background: Demand for mental health services, particularly publicly provided services, varies substantially at the local level. Accurate local es- timates of both demand and supply are essential for e¤ective planning and resource allocation. However, no data source currently provides county- level prevalence rates of mental illness within any U.S. state. Aims of the Study: In this paper, we estimate the prevalence of men- tal illness and identify potential shortages in public mental health service provision across counties in New York State. Methods: We estimate the probability of having a mental illness using a probit regression model based on demographic characteristics from the National Health Interview Survey (NHIS). These estimates are applied to population data from the American Community Survey (ACS) to gener- ate county-level prevalence estimates. We calculate mental health service de…cits as the di¤erence between estimated demand for public services and actual supply, using data from the New York O¢ ce of Mental Health 2019 (OMH). Results: Estimated prevalence of mental illness varies considerably across counties, ranging from 1.8% to 5.8%. Counties with higher average family incomes tend to exhibit lower prevalence rates. Overall, in most parts of New York, the supply of public mental health services generally meets county-level demand. Discussion and Limitations: Our prevalence-based demand estimates may understate true demand for public services, as not all individuals with mental illness seek care. Due to data limitations, we are unable to account for the size and service capacity of individual programs or to as- sess their cost-e¤ectiveness. Implications: Policymakers need accurate estimates of local mental health service needs and current provision to allocate resources e¤ectively. Better public information on local program capacity and outcomes is critical for evaluating coverage and cost-e¤ectiveness of mental health interventions.

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Abstract: We consider many ways to use K6 as an explanatory variable in equations for marriage and employment. We find that a) it is inappropriate transform K6 into a binary variable; b) it is inappropriate to add the K6 variables into a single sum of Lykert scales; c) there are serious issues associated with using each of the K6 variables separately; and d) each possible way to use K6 has critical issues making its use problematic.

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Abstract: While researchers have used the traditional index system – part of the niche-fitness model – to evaluate the innovation ecosystem, this index system can be seen as not being sufficiently objective, with the consequent problem that it gives equal weight to the indicators and so does not specify the important factors. To remedy this problem of insufficient objectivity, this paper seeks to improve the traditional niche-fitness model in two ways, which are based on the theory of the innovation ecosystem. First, by introducing the principal components analytic method to solve multiple mutual linear problems. Second, by constructing a new evaluation index system from the four aspects of openness, synergy, sustainability, and growth. This new evaluation index system is closer to the characteristics of the organic and evolutionary nature of the sustainable innovation ecosystem compared with the traditional index system. By using the evaluation index system, the research carries out a health assessment for the sustainable innovation ecosystems in different regions of provincial and municipal China from the two perspectives of descriptive and quantitative analyses. Through these analyses, our findings suggest that the sustainable regional innovation ecosystems in China are, on the whole, in an imbalance: there is a gradual decreasing trend from the eastern coastal areas to the central and western regions, and then the northeast regions.

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