Using Threshold Regression as an Approach to Incorporate Informative Missingness in Long Life Family Study Data

Genetics of aging is important since aging is a major risk factor in most diseases. Variables describing physiological state and cognitive functioning that influence morbidity and mortality risks can serve as biomarkers of aging. They change with increasing age and the ways in which these variables change can also influence these risks. Missing data due to dropout or death create problems in longitudinal studies producing biased results especially if the gap between exams is relatively long, as is the case in the Long Life Family Study (LLFS). We applied the threshold regression model to LLFS data to investigate the vitality and its rate, which are conceptualized as latent variables characterizing health and longevity, and to cope with such a problem. We performed genome-wide association study by sex and age groups to discover genetic signals on these phenotypes. We found 11 variants from the DACT2 gene, p-values < 1E-6 and variants rs12151399 (p-value = 8.43E-8, intron variant, gene AGAP1, in females), rs27958 (p-value = 8.39E-8, intron variant, gene ARHGAP26, in males) showing associations with the vitality. Olfactory receptors showed significant enrichment among the group of males over 80 years for the rate of aging phenotype. Results showed that vitality and its rate differ among sex and age groups. This work is an important step toward understanding the processes of aging linking the vitality with individual genetics using data from deceased and living individuals.

Tourism and environmental performance: New evidence using a threshold regression analysis

To verify whether the effect of tourism on environmental performance differs by the level of tourism development, a panel threshold regression approach is applied to observe the effects of tourism on environmental performance in 97 countries over the 2002–2012 periods. Our results suggest that tourism always has a significant negative influence on the environmental performance, implying that tourism will unavoidably result in environmental degradation, irrespective of how high the level of tourism development. However, when tourism development exceeds a certain value, tourism will relatively have less influence on environmental performance. In terms of policy prescriptions, considering that tourism wills inevitably worse environmental qualities, this finding implies that policymakers should consider the optimal level of tourism development at around the estimated threshold level to minimize the negative impact of tourism on environmental quality.

The Nonlinear Links Between Urbanization And CO2: Evidence From Unconditional Quantile And Threshold Regression

The extant literature has provided empirical evidences about the relationship between urbanization and environment, however, a little attention has been paid to non-linear relationship among them. This study aims to measure the effects of urbanization on carbon dioxide emission using quantile and threshold regression method. To this end, the study employed threshold analysis and quantile regression method and analyzed the variation of such non-linearity for different levels of carbon dioxide using quantile regression. The results illustrate that a single threshold and two regimes exist and the threshold for urbanization is 29.56%. Across both regimes, the elasticity estimates form an inverted U-shape impact of urbanization on the carbon dioxide emission. The increase in the marginal effect of urbanization on carbon dioxide emissions up to the median level and a declining trend after this level implies that environmental quality significantly improves for emerging country.

Research on Regional Differences of the Leisure Agriculture’s Impact on Farmers’ Income—An Empirical Analysis Based on Nonlinear Threshold Regression

As a large agricultural country and a populous country, the development of agricultural and rural areas is the foundation for China to realize a national rejuvenation. Leisure agriculture is the main carrier of industry integration in China’s rural areas and it is an effective means to realize rural revitalization and increase farmers’ income. Industry convergence refers to a dynamic development process in which different industries or different areas of the same industry penetrate and intersect each other and finally merge into one, gradually forming a new industry. However, there is no empirical study on the staged impact of rural agriculture on rural household income and regional differences. This article breaks down the action mechanisms, analyzes the linear impact of leisure agriculture on the income of farmers and divides the development types of leisure agriculture according to the characteristics of leisure agriculture development. Using the provincial panel data from 2008 to 2016, the panel dual-threshold regression model was used to verify the regional differences in the impact of leisure agriculture on farmers’ income, from the perspective of leisure agriculture on farmers’ nominal and actual incomes. Then, the robustness model was used to test leisure agriculture’s impact on farmers’ income. The results show that the impact of leisure agriculture on the income of farmers is staged. Among them, the impact of leisure agriculture on the nominal income of farmers is an “inverted U-shaped” structure and the impact on actual income is an “N-type” structure. At the same time, the paper also finds that the regional differences in the impact of leisure agriculture on farmers’ income are significant and the constraints on the development of leisure agriculture in different regions are different. Based on this, it is proposed that the government should respond to the different development stages of leisure agriculture according to the time, and according to the different development areas of leisure agriculture. Responses should also be based on local conditions, and work to strengthen the participation of farmers.