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on Central and Western Asia |
| By: | Ira N. Gang (Department of Economics, Rutgers University); Kseniia Gatskova (IOS-Regensburg); John Landon-Lane (Department of Economics, Rutgers University); Myeong-Su Yun (Department of Economics, Inha University) |
| Abstract: | We examine vulnerability to poverty in Tajikistan during the global financial crisis, focusing on the roles played by international migration and remittances, using a formal, practical, and easily decomposable vulnerability measure. Our strategy is to estimate a Markov transition probability matrix with the aim of identifying the vulnerability of households to poverty. Importantly, by introducing the index of vulnerability as the weighted probability of a household falling into poverty over a given time horizon, we can use the estimated dynamics to assess the short, medium and long-run vulnerability. We find that during the "recession transition" almost all households were vulnerable to poverty while almost none were during the "recovery period". Overall, urban households, more educated households and households receiving remittances from international labor migrants were less vulnerable to poverty. While households with a current or very recent migrant did not have a significantly lower measured vulnerability to poverty, those households receiving remittances from migrants had a lower vulnerability to poverty. Our findings stress that the international labor migration from Tajikistan may not be considered as a reliable means of welfare security for the households because external economic shocks and internal political decisions may negatively affect Russian economy and lead to a reduction of remittances flow to Tajikistan. |
| Keywords: | mobility measurement, vulnerability, poverty, inequality, measurement, Tajikistan |
| JEL: | J60 D63 I32 |
| Date: | 2017–04 |
| URL: | http://d.repec.org/n?u=RePEc:inh:wpaper:2017-2&r=cwa |
| By: | Lyazzat Nugumanova |
| Abstract: | Kazakhstan has one of the highest CO2 emissions per GDP in the world. Kazakhstan has taken a leadership role in the Central Asian region in terms of climate change policies and greener economy. Kazakhstan has ratified Kyoto Protocol in 2009. Kazakhstan has committed to reduce emissions by 15% below 1992 GHG levels by year 2020. In 2013 by decree of President of Kazakhstan a concept of Green Growth was adopted. Environmental regulations in Kazakhstan inherited from the planned economy need to be modified to correspond to current economic situation and climate change goals. Carbon tax and emissions trading are two of the main instruments to curb GHG emissions. There is an ongoing debate regarding which policy instrument is the most optimal towards reduction of emissions. The main difference between the two instruments are levels of uncertainty with regards to the carbon price and thus emissions reductions. Carbon tax provides more carbon price certainty, while emissions trading carbon prices are more volatile. Carbon tax mechanism is more easily to implement and operate, than ETS. Kazakhstan has opted and implemented emissions trading scheme in January 2013.. The ETS covers 55% of total CO2 emissions in Kazakhstan, and includes energy, mining and chemical industry. The average price of allowances was KZT 406 (US$2). Carbon tax in Kazakhstan would provide stability of carbon price, moreover carbon tax is easier to implement and monitor. The objective of this paper is using computable general equilibrium (CGE) model evaluate macroeconomic and environmental impacts of different carbon tax levels in Kazakhstan. Standard multiregion, multisector static CGE model, GTAP is used to simulate the impact of different carbon tax levels in Kazakhstan. GTAP is a standard CGE model based on assumptions of perfect competition and constant returns to scale. GTAP data base with latest version 9 is used in this study. The base year of the data base is 2010. The data base for the purpose of this study is aggregated to 11 sectors, out of which six are energy sectors, and six regions. Six regions are Kazakhstan, Russia, Belarus, China, EU and Rest of the World. Three sets of scenarios are simulated where carbon tax is priced at US$5, US$10 and US$20 per tCO2. Carbon tax is implemented in the CGE model as ad valorem equivalents. Carbon tax is implemented for all energy sectors and chemicals and heavy manufacturing sectors. Initial findings show macroeconomic effects of carbon tax in Kazakhstan. Preliminary findings allow to identify sectors which would benefit or loss from the implementation of carbon tax in Kazakhstan. It is expected that in all scenarios CO2 emissions will reduce, though magnitude of CO2 emissions reductions is expected to differ. |
| Keywords: | Kazakhstan, Energy and environmental policy, General equilibrium modeling |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9175&r=cwa |
| By: | Alper Duman |
| Abstract: | Trade among the cities of a country is similar to international trade in various aspects. Recently there is a surge of studies focusing on the network characteristics of international trade. We extend the main idea and the methodology of these studies to the inter-city trade network in Turkey in order to model and trace the network spillovers of a given shock (i.e. intensification of Syrian conflict and hence the drop of income in Southeastern cities) on the overall income and intercity trade volume. ntercity trade can be considered as a network. This trade network can be represented as a directed, weighted, incomplete, and asymmetric graph in which each city is a node and the bilateral trade links are the edges. The network is directed as each city is unlikely to trade at equal amounts from each other. The network is weighted because all links reflect some value of payment that is different for each city and each flow. The network is incomplete as not all cities in Turkey are connected with each other through trade. Finally, the network is asymmetric because for most cities customer partners (out-links) differs from the number of supplier partners (in-links). The ministry of Science, Technology and Industry provides intercity trade data for the year 2013. First we construct the intercity trade network derived from the data. Second we follow, Kireyev and Leonidev (2015) method to model and trace the network spillovers of a given shock (i.e. intensification of Syrian conflict and hence the drop of income in Southeastern cities) on the overall income and intercity trade volume. The main insight of the network modelling approach is the following. Once a source city faces a shock in terms of income loss, its purchases from its first neighbour cities will be affected. Then the these cities will face adverse effects in terms of income and so their neighbour cities will have to bear the spillover effects. This network contagion will have an aggregate effect which will be larger than the direct effect. Ten percent drop in income of the Southeastern cities which constitute about 10 % of the GDP of Turkey will have a significant effect on the overall income and inter-city trade volume in Turkey |
| Keywords: | Turkey, Modeling: new developments, Trade issues |
| Date: | 2016–07–04 |
| URL: | http://d.repec.org/n?u=RePEc:ekd:009007:9578&r=cwa |
| By: | Javorcik, Beata; Lo Turco, Alessia; Maggioni, Daniela |
| Abstract: | This paper examines the relationship between the presence of foreign affiliates and product upgrading by Turkish manufacturing firms. The analysis suggests that Turkish firms in sectors and regions more likely to supply foreign affiliates tend to introduce more complex products, where complexity is captured using a measure developed by Hausmann and Hidalgo (2009). This finding is robust to controlling for omitted variables, sample selection and potential simultaneity bias. It is also in line with the view that inflows of foreign direct investment stimulate upgrading of indigenous production capabilities in host countries. |
| Keywords: | Backward Linkages; FDI; Product Innovation; Production Upgrading; Turkey |
| JEL: | D22 F23 L20 |
| Date: | 2017–03 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:11942&r=cwa |