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on South East Asia |
| By: | Chirwa, Themba G; Odhiambo, Nicholas M. |
| Abstract: | This paper examines the short- and long-run relationship between economic growth and electricity consumption as an additional factor of production where state and macroeconomic stability variables are included in a multivariate growth model. The study uses the Autoregressive Distributed Lag (ARDL) approach to cointegration to investigate this relationship in twelve countries during the period 1970-2014, selected from three continents, namely: Europe (Luxemborg, Norway, Denmark, Belgium), Asia (Singapore, Japan, Indonesia, India), and Africa (South Africa, Algeria, Egypt, Kenya), representing developed and developing countries. The study results reveal that electricity consumption is positively and significantly associated with economic growth in Luxemborg, Norway, Denmark, Belgium, Japan, Indonesia, India, South Africa, Algeria, and Egypt; and negatively associated with economic growth in Kenya in the long run. In the short run, the results reveal a positive and significant association between electricity consumption and economic growth in Luxemborg, Denmark, Singapore, Japan, Indonesia, India, South Africa, and Algeria; and negatively associated in Egypt. The study therefore concludes that electricity consumption is an important factor of production in the study countries. Therefore, policy makers in economies where energy use leads to economic growth should focus on growth-promoting energy policies that are supported by macroeconomic stability policies. |
| Keywords: | Electricity Consumption; Macroeconomic Stability; Exogenous Growth Models; Autoregressive Distributed Lag Model; Europe; Asia; Africa |
| Date: | 2018–01–11 |
| URL: | http://d.repec.org/n?u=RePEc:uza:wpaper:23508&r=sea |
| By: | Minh Ha-Duong (CIRED - Centre International de Recherche sur l'Environnement et le Développement - CIRAD - Centre de Coopération Internationale en Recherche Agronomique pour le Développement - EHESS - École des hautes études en sciences sociales - AgroParisTech - ENPC - École des Ponts ParisTech - CNRS - Centre National de la Recherche Scientifique); Hoang Anh Trinh Nguyen (CleanED - Clean Energy and Sustainable Development Lab - USTH - University of sciences and technologies of hanoi) |
| Abstract: | Vietnam plans to develop dozens of new coal-fired power generation units over the next 20 years. If they are indeed build, in order to avoid a dangerous level of global warming, it may appear necessary to dispose of these plants' CO2 by burying it in deep underground geological formations instead of releasing it into the atmosphere, using carbon capture and storage (CCS) technology. We show that CCS has a technical potential in Vietnam, according to the geology and the industrial geography. To discuss under which economics conditions this potential could actualize, we examine two scenarios for 2050. In the first scenario, CO2 is used in Enhanced Oil Recovery (EOR) only. EOR technology makes CCS cheaper by injecting CO2 in partially depleted oil field, aiming to recover more oil. The second scenario considers CCS deployment in coal-based power plants, on top of using it for EOR. In both scenarios, a few gas-fired CCS power plants are build, reaching 1 GW in 2030, supported by Enhanced Oil Recovery and international carbon finance. The decision point where the two scenarios diverge is in 2030. A scenario to switch all currently existing or planned power plants to low-carbon by 2050 is to retrofit 3.2 GW of coal-fired capacity and install 1.2 GW of gas-fired capacity with CCS every year, starting in 2035 for 15 years. Capture readiness would lower the costs of using CCS in Vietnam, but is not mandatory today. |
| Keywords: | Vietnam,Scenario,Power generation,Carbon capture and storage,Capture ready |
| Date: | 2017–11 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01597515&r=sea |
| By: | Porzio, Tommaso; Santangelo, Gabriella |
| Abstract: | What explains labor reallocation out of agriculture? We show that decreases in the supply of agricultural workers, due to younger birth-cohorts having skills which are more valued out of agriculture, play a major, and previously overlooked, role. First, we use micro data from 52 countries to decompose aggregate labor reallocation into year and cohort effects. Cohort effects accounts for more than half of overall reallocation. Then, we develop an overlapping generations model to provide an analytical and parsimonious map from the statistical objects, year and cohort effects, into the structural objects of interest, demand and supply of agricultural workers. The map is modulated by mobility frictions and general equilibrium, which we discipline with micro data. Filtering the data through the model, we conclude that decreases in the supply of agricultural workers account for a sizable fraction, approximately one third, of labor reallocation. Finally, we show that, both within and across countries, larger increases in schooling across cohorts are correlated with faster reallocation out of agriculture, suggesting that human capital determines the supply of agricultural workers. We provide further, and causal, evidence on the role of human capital by showing that a school construction program in Indonesia led to labor reallocation out of agriculture. |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:cpr:ceprdp:12495&r=sea |
| By: | Sarah Smith (Institute for Fiscal Studies and University of Bristol); Mark Ottoni-Wilhelm (Institute for Fiscal Studies); Kimberley Scharf (Institute for Fiscal Studies and University of Warwick) |
| Abstract: | Natural disasters, such as the 2004 East Asian Tsunami, attract a high level of donations. Previous literature has shown that the scale of the disaster is important in driving the aid response, but there are inconsistent findings on whether the number killed or the number affected matters more. In this paper we discuss a number of issues in linking measures of the scale of a disaster to the aid response, particularly taking account of outliers in both scale of disaster and aid. We show that a log-specification is preferred and that this specification can reconcile findings based on different datasets. Both the number killed and the number affected matter equally for whether aid is given; the number killed is more strongly related to the magnitude of the aid response. We also present new evidence confirming the importance of publicity for disasters, focusing on appeals. |
| Date: | 2017–10–04 |
| URL: | http://d.repec.org/n?u=RePEc:ifs:ifsewp:17/19&r=sea |
| By: | An Truong (CleanED - Clean Energy and Sustainable Development Lab - USTH - University of sciences and technologies of hanoi) |
| Date: | 2017–11–06 |
| URL: | http://d.repec.org/n?u=RePEc:hal:journl:hal-01638613&r=sea |
| By: | Agaton, Casper |
| Abstract: | With the continuously rising energy demand and much dependence on imported fossil fuels, the Philippines is developing more sustainable sources of energy. Renewable energy seems to be a better alternative solution to meet the country’s energy supply and security concerns. Despite its huge potential, investment in renewable energy sources is challenged with competitive prices of fossil fuels, high start-up cost for renewables, and lower feed-in-tariff rates for renewables. To address these problems, this study aims to analyze energy investment scenarios in the Philippines using real options approach. This compares the attractiveness of investing in renewable energy over continue using coal for electricity generation under uncertainties in coal prices, investments cost, electricity prices, growth of investment in renewables, and imposing carbon tax for using fossil fuels. |
| Keywords: | real options approach; investment under uncertainty; dynamic optimization; renewable energy |
| JEL: | C61 G17 Q42 Q47 |
| Date: | 2017–12–30 |
| URL: | http://d.repec.org/n?u=RePEc:pra:mprapa:83478&r=sea |
| By: | Gupta, Bishnupriya (University of Warwick) |
| Abstract: | India fell behind during colonial rule. The absolute and relative decline of Indian GDP per capita with respect to Britain began before colonization and coincided with the rising textile trade with Europe in the 18th century. The decline of traditional industries was not the main driver Indian decline and stagnation. Inadequate investment in agriculture and consequent decline in yield per acre stalled economic growth. Modern industries emerged and grew relatively fast. The falling behind was reversed after independence. Policies of industrialization and a green revolution in agriculture increased productivity growth in agriculture and industry, but Indian growth has been led by services. A strong focus on higher education under colonial policy had created an advantage for the service sector, which today has a high concentration of human capital. However, the slow expansion in primary education was a disadvantage in comparison with the high growth East Asian economies |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:wrk:warwec:1147&r=sea |
| By: | Gupta, Bishnupriya (University of Warwick) |
| Abstract: | India fell behind during colonial rule. The absolute and relative decline of Indian GDP per capita with respect to Britain began before colonization and coincided with the rising textile trade with Europe in the 18th century. The decline of traditional industries was not the main driver Indian decline and stagnation. Inadequate investment in agriculture and consequent decline in yield per acre stalled economic growth. Modern industries emerged and grew relatively fast. The falling behind was reversed after independence. Policies of industrialization and a green revolution in agriculture increased productivity growth in agriculture and industry, but Indian growth has been led by services. A strong focus on higher education under colonial policy had created an advantage for the service sector, which today has a high concentration of human capital. However, the slow expansion in primary education was a disadvantage in comparison with the high growth East Asian economies |
| Keywords: | JEL Classification: |
| Date: | 2018 |
| URL: | http://d.repec.org/n?u=RePEc:cge:wacage:355&r=sea |
| By: | Wang, Wuyi (School of Economics, Singapore Management University); Su, Liangjun (School of Economics, Singapore Management University) |
| Abstract: | We propose a procedure to identify latent group structures in nonlinear panel data models where some regression coefficients are heterogeneous across groups but homogeneous within a group and the group number and membership are unknown. To identify the group structures, we consider the order statistics for the preliminary unconstrained consistent estimators of the regression coefficients and translate the problem of classification into the problem of break detection. Then we extend the sequential binary segmentation algorithm of Bai (1997) for break detection from the time series setup to the panel data framework. We demonstrate that our method is able to identify the true latent group structures with probability approaching one and the post-classification estimators are oracle-efficient. The method has the advantage of more convenient implementation compared with some alternative methods, which is a desirable feature in nonlinear panel applications. To improve the finite sample performance, we also consider an alternative version based on the spectral decomposition of certain estimated matrix and link the group identification issue to the community detection problem in the network literature. Simulations show that our method has good finite sample performance. We apply this method to explore how individuals' portfolio choices respond to their financial status and other characteristics using the Netherlands household panel data from year 1993 to 2015, and find three latent groups. |
| Keywords: | Binary segmentation algorithm; clustering; community detection; network; oracle estimator; panel structure model; parameter heterogeneity; singular value decomposition. |
| JEL: | C33 C38 C51 |
| Date: | 2017–12–16 |
| URL: | http://d.repec.org/n?u=RePEc:ris:smuesw:2017_019&r=sea |
| By: | Takeshi Kawakatsu; Soochoel Lee; Sven Rudolph |
| Date: | 2017–12 |
| URL: | http://d.repec.org/n?u=RePEc:kue:epaper:e-17-009&r=sea |