Broadly Distributed but Genetically Fragmented: Demographic Consequences of Pleistocene Climatic Oscillations in a Common Iberian Grasshopper

Although the genetic consequences of contemporary landscape composition and range shifts driven Pleistocene climatic oscillations have been studied fairly well in alpine organisms, we know much less about how these factors have shaped the demography of taxa with broader climatic niches and distributions. Here, we use high-throughput sequencing data to study the processes underlying spatial patterns of genomic variation in Omocestus panteli (Bolívar, 1887) (Orthoptera: Acrididae), a common Iberian grasshopper distributed across numerous habitat types and a wide elevational range (from sea level to >2,000 m). Although the species is broadly distributed, our analyses support that its contemporary populations show significant genetic fragmentation that dates back to the last glacial period. Accordingly, spatially explicit testing of alternative gene flow scenarios and demographic inference analyses revealed that genetic differentiation between populations and their long-term effective population sizes are best explained by the spatial configuration of environmentally suitable habitats during the last glacial maximum (ca. 21 ka). At that time, the species experienced net demographic expansions but interspersed unsuitable areas might have disrupted gene flow and created opportunity for geographical diversification. Collectively, our analyses indicate that the genetic makeup of contemporary populations is not well explained by current environmental factors or geographical barriers to dispersal but mostly reflects genetic fragmentation during the last glacial period followed by postglacial admixture among previously isolated gene pools. Taken together, these results support that the Pleistocene ‘species pump’ model might be also useful in explaining demographic dynamics and geographical diversification in taxa characterized by broad climatic niches.

The Moderating Role of Geographical Diversification among the Nexus of Institutional, Power and Space Factor on Economic Geography

The present paper aims to explore the relationships among the institutional factor, power factor, space factor and economic geography in Poland. The goal of the study also consists of the examination of the moderating role of geographical diversification among the nexus of institutional factor, power factor, space factor and economic geography in Poland. The data has been gathered by using primary data collection methods and used survey questionnaires for data collection along with simple random sampling to select the respondents and PLS-SEM for data analysis. The results revealed that institutional factor, power factor, space factor have a positive association with economic geography in Poland. The outcomes also concluded that the geographical diversification is moderating among the nexus of institutional factor, power factor, space factor and economic geography in Poland. These findings are suitable for the regulators that they should focus on institutional power and space factor that would improve the economic geography in Poland.

Does the target market affect bank performance? Evidence from the geographic diversification of city commercial banks in China

After the opening up of the banking sector to domestic and foreign capitals which is approved by the Chinese government, the China Banking Regulatory Commission (CBRC) has permitted city commercial banks to diversify geographically. Since this deregulation in 2006, city commercial banks began to geographically diversify to occupy the market and acquire more financial resources. To examine the causal relationship between geographical diversification and bank performance, we construct an exogenous geographical diversification instrument using the gravity-deregulation model and a policy shock. We find that bank geographical diversification negatively affects bank performance. Moreover, we conduct some mechanism tests in the Chinese context. We find that the target market with several large- and medium-sized banks and a high level of local protectionism in the target market decreases the performance of city commercial banks. Finally, cross-sectional analyses show that the impact of geographical diversification on banks’ performance is more notable among city commercial banks that are younger, and have a lower capital adequacy ratio and a higher non-performing loan ratio.

GEOGRAPHICAL DIVERSIFICATION AND LONGEVITY RISK MITIGATION IN ANNUITY PORTFOLIOS

ABSTRACT This paper provides a method to assess the risk relief deriving from a foreign expansion by a life insurance company. We build a parsimonious continuous-time model for longevity risk that captures the dependence across different ages in domestic versus foreign populations. We calibrate the model to portray the case of a UK annuity portfolio expanding internationally toward Italian policyholders. The longevity risk diversification benefits of an international expansion are sizable, in particular when interest rates are low. The benefits are judged based on traditional measures, such as the Risk Margin or volatility reduction, and on a novel measure, the Diversification Index.

Effects of geographical and technological diversification on the development of spatially disaggregated wind and solar power market values

<p><strong>Keywords</strong>: Market value, Technological diversification, Geographical diversification, Spatial value factor distribution</p><p>Ambitious climate and energy targets require environmentally compatible energy generation with a high utilisation of renewable energy sources. However, due to the intermittent appearance of wind and PV feed-in, variable renewable energy (VRE) reveals significantly lower market values than conventional dispatchable power (Joskow, 2011). Additionally, with higher VRE shares a significant market value drop of wind and solar power has been observed in recent years as a result of the merit order effect (Hirth, 2013). Moreover, results by Engelhorn and Müsgens (2018) and Becker and Thrän (2018) have indicated regional disparities in empirical market values for Germany.  This poses interest on what exactly drives and how to quantify the development and spatial distribution of VRE market values.</p><p>Against this background, an electricity market model is applied to trace the development of spatial market values based on model-endogenous electricity prices. A special feature of the model is the inclusion of highly regionally disaggregated weather data which allows to investigate effects of different geographical and technological VRE diversification strategies in Germany until 2035 (Eising et al., 2020). The results of this research are threefold:</p><ul><li>Technological diversity: results show a significant decrease in PV and onshore wind value factors as VRE shares increase. Replacing onshore wind energy by offshore wind energy reduces the volatility and counteracts the value drop of onshore wind, offshore wind and PV.</li> <li>Geographical diversity: results indicate that geographical diversification does not necessarily mitigate decreasing VRE value factors. Under specific circumstances, a higher concentration at sites with lower full-load hours and corresponding higher feed-in volatility potentially mitigates positive effects from more spatially distributed generation.</li> <li>Spatial distribution of value factors: for all mitigation strategies and for wind and PV the spatial value factor distribution shows future increases in regional disparities. However, regional value factor disparities are most distinct in case of onshore wind. The analysis reveals two significant drivers: first, a negative relationship between the regional wind capacity density and their regional value factors can be observed. Second, results indicate a negative relationship between site-specific wind feed-in volatility and the value factor.</li> </ul><p> Summarising, the analysis highlights the importance of considering spatial market values in efficiently designing future electricity markets.  </p><p> </p><p><strong>References</strong></p><p>Becker, R., Thrän, D., 2018. Optimal Siting of Wind Farms in Wind Energy Dominated Power Systems. Energies 11, 978. https://doi.org/10.3390/en11040978</p><p>Eising, M., Hobbie, H., Möst, D., 2020. Future wind and solar power market values in Germany — Evidence of spatial and technological dependencies? Energy Econ. 86, 104638. https://doi.org/10.1016/j.eneco.2019.104638</p><p>Engelhorn, T., Müsgens, F., 2018. How to estimate wind-turbine infeed with incomplete stock data: A general framework with an application to turbine-specific market values in Germany. Energy Econ. 72, 542–557. https://doi.org/10.1016/j.eneco.2018.04.022</p><p>Hirth, L., 2013. The market value of variable renewables: The effect of solar wind power variability on their relative price. Energy Econ. 38, 218–236.</p><p>Joskow, P.L., 2011. Comparing the Costs of Intermittent and Dispatchable Electricity Generating Technologies. Am. Econ. Rev. 101, 238–241.</p>