Awareness of climate change: differences among Russian regions

Abstract

This thesis reveals methods for estimating individual perception at the regional level, such as environmental awareness or wage effects due to labour market tightness. Environmental awareness belongs to individual attitudes, which is driven by socialization, culture and education. Consequently, it is difficult to compare environmental awareness between regions. Labour market tightness might be reflected in individual wages, but the latter is also triggered by a lot of exogenous variables. Given that a simple linear regression model fails in both cases, existing alternative approaches from the econometrics like Multiple Indicator Multiple Cause model and Least Absolute Shrinkage and Selection Operators are used.First, a Multiple-Indicator Multiple-Causes model is introduced, which allows us to estimate a not-directly observable individual attitude, environmental awareness, for different regions and to rank them. The method is cost-effective and less time-consuming, it also allows for comparisons between regions. The study area serves 81 regions in Russia. The model is constructed in such a way that Internet queries from the search engine c Yandex are assumed to be indicators, which are affected by the regional environmental awareness index. In addition, regional characteristics, such as Gross Regional Product per capita, the proportion of employees in specific industry sectors, and also the environmental situation within the regions are potential cause variables. The regional environmental awareness index is estimated for each of the Russian regions from January 2014 until April 2016. Furthermore, the findings shows a rather non-linear positive relationship between the regional environmental awareness and regional wealth, as well as a strong negative correlation with the temperature. The colder the region and the observed month, the higher the interest of the population in environmental topics. Furthermore, the regions can be grouped into four environmental awareness clusters by using k-means clustering algorithm. It seems that the environmental awareness index shrinks from the Eastern to the Western part of Russia. The highest values can be estimated in Chukotka, Kamchatka, and Magadan. The lowest values are found in the rather poor and warm Caucasus area.Second, another issue concerns the estimation of an effect of an observable regional variable, such as labour supply shortage, on individual wages. This thesis investigates the ten year wage development of employees who first enter the labour market from 1995 until 2004 and looks for positive wage effects of labour market tightness in different occupational groups. Due to incomplete vacancy data, labour market tightness is measured as the number of unemployed people divided by the number of employees within an occupational field and region. Mean and quantile regression methods are applied. Because the number of right-hand side variables could lead to incorrect detected statistical significant coefficients, different Least Absolute Shrinkage and Selection Operato...

Waxing power, waning pollution: The effect of COVID-19 on Russian environmental policymaking

“…Finally, we employ the Yandex Self-Isolation Index, recently developed by Yandex, the leading technological company in Russia which offers applications and services for both business and private users, including a search engine, navigation products, transportation services, logistics, human resources services, corporate health insurance, and online sales registers. 12 Yandex search data have previously been used in research on climate change in Russia, see Losch et al (2019) , but their self-isolation index was launched in February 2020 and has not been utilized before. The Index is calculated based on the use of various services and mobile applications of Yandex and ranges from 0 (no self-isolation) to 5 (complete self-isolation).…”

Geographies of climate change opinion

“…While we can learn from individual case studies that CCOs are locally embedded and can vary substantially across sub-national regions, a comparative perspective is less common in these detail-rich studies. Notable exceptions are studies on Russia (Lösch et al, 2019) and on the USA by Hamilton and Keim (2009) and Howe et al (2015), as well as Hamilton et al (2016) who find ample variation in CCA across metropolitan areas and counties in the USA. However, the papers offer little explanation and contextualisation of their findings and focus on geographically rather large countries.…”

“…While we can learn from individual case studies that CCOs are locally embedded and can vary substantially across sub‐national regions, a comparative perspective is less common in these detail‐rich studies. Notable exceptions are studies on Russia (Lösch et al., 2019) and on the USA by Hamilton and Keim (2009) and Howe et al. (2015), as well as Hamilton et al.…”