Migration impact on left-behind women's labour participation and time-use: Evidence from Kyrgyzstan

This paper aims to study the impact of migration on labour supply and time-use of women left behind in Kyrgyzstan. Using the household survey data for 2011, labour supply is measured by occupational choices and working hours. Apart from the labour supply data, this study uses detailed information on daily time-use, which is analysed within women's occupations. This approach makes it possible to indicate the impact of migration not only through the labour supply analysis, which may be limited by reflecting labour market behaviour only, but also through the measure of allocation of time among different activities at home. To address the issue of endogeneity, the instrumental variable approach is applied. Results show that the migration of a household member increases the choice of left-behind women to be unpaid family workers. Most of the left-behind women choose unpaid family work and work more hours in this occupation. Although in the labour supply analysis wage-employment is not affected by migration, time-use model estimations reveal that wage-employed women are mostly affected through increases in the time for housework

Yapay Sinir Ağları Yöntemi ile Menkul Kıymetler Borsası Endeksinin Değişim Yönü Tahmini: İstanbul Menkul Kıymetler Borsası Örneği

DergiPark: 326237trakyasobedThis study aims to examine performance of artificial neural networks (ANN) in forecasting stock market index movement. The forecasting is based on two samples of Istanbul Stock Exchange (ISE) data and each consisting of 150 observations. Forecasting performance is assessed in one, five and ten day periods. Results show that ANN gives high percentage of correctly forecasted signs. This performance is particularly evident in five days period, while conventional approach mostly uses next day forecasting. These results imply that for more efficient forecasting with ANN use of different time periods is importantBu çalışma yapay sinir ağları yönteminin menkul kıymetler borsa endeksinin değişim yönünü tahmin etme başarısını incelemeyi amaçlamaktadır. Tahminde Istanbul Menkul Kıymetler Borsası (İMKB) verilerinden oluşturulan ver her biri 150 gözlemden oluşan iki örneklem kullanılmıştır. Sonuçlar yapay sinir ağlarının endeks değişimlerinin yüksek yüzdesinin doğru tahmin ettiğini göstermektedir. Sözkonusu performans özellikle beş günlük periodda daha yüksek çıkmıştır. Oysa birçok çalışmada geleneksel yaklaşım olarak bir sonraki gün değeri tahmin edilmeye çalışılmıştır. Bu çalışma sonuçlarına göre yapay sinir ağları ile daha etkin tahmin yapabilmek için farklı zaman periodlarının dikkate alınması önemli olmaktadı

Determinants of export performance of SMEs in the Kyrgyz Republic

Increased participation in global value chains is firmly related to the engagement of local producers in international markets through increasing sales in these markets. This study aims to examine factors affecting export performance of SMEs in the Kyrgyz Republic. Empirical estimations based on the Enterprise Survey data set reveal that correspondence with quality requirements, increasing participation of foreign capital in ownership of firms, availability of financial resources, and labor productivity are important determinants of exporting activities of SMEs. Along with this, firms in industries with a low technology level demonstrate relatively higher export activities. However, it can also be argued that SMEs do not have enough capability to adopt medium and high technology in their production process, which may lead to concern over the long-term sustainability of their competitiveness in international markets. These findings underline that government policy towards enhancing labor productivity, foreign capital participation associated with the higher availability of financial resources, and knowledge-supporting programs are important for the export of SMEs in the Kyrgyz Republic

Measuring the impact and financing of infrastructure in the Kyrgyz Republic

This study examines the impact of the Osh-Sarytash-Irkeshtam and Sarytash-Karamyk road construction projects in the Kyrgyz Republic on regional social and economic development. Discussions of financing infrastructure in the Kyrgyz Republic context are also provided. Evaluation of impact is based on estimations from the panel dataset for the period 2005-2017 using both regional and district-level information. The findings indicate that the road construction projects had a positive effect on poverty reduction and retail trade growth, which was especially evident in the sample of two mountainous districts. The long-term sustainable economic effects of road construction require the creation of a business ecosystem along the road. International road construction should be accompanied by external trade promotion initiatives and the reduction of barriers at borders. The efficiency of road infrastructure also depends on improved regional cooperation, which necessitates consideration of the road not only as a transit or transport corridor, but also more comprehensively as an economic corridor with a potential wider economic effect. The development of public-private partnership for infrastructure investment is another strategic direction for government policy, which should be associated with policies to decrease regulatory burden, private investment risk, and increase institutional development

The impact of infrastructure on Trade in Central Asia

The aim of this paper is to investigate the impact of infrastructure on trade in the case of Central Asian countries. Infrastructure is measured by the aspects of quality and quantity in three Central Asian countries - Kazakhstan, the Kyrgyz Republic, and Tajikistan. Trade flows are measured by the export and import volumes of each of these countries with their main trade partner countries. Empirical estimations are based on panel data for the period 2009-2017. Results show that both the quality and quantity of infrastructure in Central Asia have a positive impact on trade flows. However, estimations by country subsamples show that this effect varies by country. Given the general remote geographical location of Central Asian countries, the findings of this study indicate that a regional approach to the development of infrastructure is important and policy towards infrastructure development should be associated with a further regional economic integration process

Gender differences, risk attitude and entrepreneurship in Kyrgyzstan

This study analyses the role of risk attitude for entrepreneurship by gender differences in Kyrgyzstan. Logit analysis is applied to the cross-sectional data set drawn from the nationally representative survey for 2011. Entrepreneurship is measured by the self-employment activities and analysed by the agricultural and non-agricultural sample. Results of the study show that more risk-taking preferences are associated with higher entrepreneurship probability. However, this effect is not persistent for women in further estimations for non-agricultural entrepreneurship sample, while for men higher positive effect of risk loving behavior remains in off-farm self-employment too. These findings underline the existing difference in risk tolerance by gender in non-agricultural employment. Movement of women from farm to off-farm entrepreneurship may not necessarily require risk loving characteristics. However, further analysis of this difference should take into account potential difference of necessity and opportunity entrepreneurs by gender

Household energy consumption behaviors during the Covid-19 pandemic in Mongolia

This investigation examines the impact of COVID-19 on households in Mongolia, particularly the choice of fuel for heating and cooking and awareness about harmful effects of indoor pollution due to the combustion of solid fuels for heating and cooking. This study uses publicly available MICS Plus survey data from UNICEF. MICS Plus is a longitudinal household survey with a sample of 2,000 representative households that collects information through telephone interviews. We compare data from a pre-COVID period (2018) and during the COVID-19 pandemic (December 2020). Our results show that households where the decision maker is female are more likely to have a clean source of heating-a district heating system. The results also show that a larger proportion of households switched to cleaner heating in the COVID-19 period. First, the share of households using central heating increased in 2020 to 26% from 19% in 2018. Second, the share of households using improved fuel for their heating requirements increased in 2020 as compared to 2018. Third, in December 2020, after the beginning of the COVID-19 pandemic, households were more likely to use district heating and manufactured space heaters than cooking stoves for heating compared to 2018

Navigating WASH challenges in rural areas: Peer effects and infrastructure

Despite the well-documented benefits of improved sanitation and washing facilities, a considerable number of people, even in middle-income countries, still lack access to modern sanitation and home-based bathing facilities. This paper leverages household budget survey data from two Central Asian countries to investigate the barriers to improved adoption of sanitation and washing facilities. The study finds that in Kazakhstan, households with higher incomes generally have better sanitation facilities. Households led by married individuals have better facilities in both Kazakhstan and the Kyrgyz Republic. The average adoption rate in a sub-province also contributes to an increased household-level sanitation and washing facilities uptake. This suggests that peer influences represent an important mechanism underlying household behavior. The role of infrastructure is significant. Access to piped water increases the probability of adoption of modern sanitation and washing facilities in both countries. Primary barriers to the adoption of better sanitation and washing facilities by rural households include the lack of necessary infrastructure (piped water and centralized sewerage)

What determines the adaptation of enterprises to COVID-19 in CAREC member countries: Empirical evidence from Azerbaijan, Georgia, Kazakhstan, and Mongolia

This study empirically investigated the factors affecting firms' ability to adjust production in response to the COVID-19 outbreak. This study used firm-level survey data from the Enterprise Survey implemented by the World Bank Group, including a standard Enterprise Survey (Baseline) and two waves of Follow-up Surveys conducted in 2020 and 2021, which included questions related to COVID-19 and firm behavior during the pandemic. We used data from four CAREC member countries: Azerbaijan, Georgia, Kazakhstan, and Mongolia. Using a probit model, we studied how different factors, including firm characteristics and government policy, affected the probability that a firm would be able to adjust its activities to the changed conditions. The results showed that firms which successfully adapted to the COVID-19 crisis were younger, foreign firms that had been innovative in the recent past, with female managers, a formal firm strategy with key performance indicators, and their own website