Long-Term Increases and Recent Slowdowns of CO2 Emissions in Korea

Korea is one of the fastest-growing CO2-emitting countries but has recently experienced a dramatic slowdown in emissions. The objective of the study is to examine the driving factors of long-term increases (1990–2015) and their slowdown (2012–2015) in emissions of Korea. This study uses an extended index decomposition analysis model that better fits Korea’s emission trends of the last 25 years by encompassing 19 energy end-use sectors (18 economic sectors and a household sector) and three energy types. The results show that emission increases in the long term (1990–2015) come from economic growth and population growth. However, improvements in energy intensity, carbon intensity, and economic structure offset large portions of CO2 emissions. The recent slowdown (2012–2015) mainly resulted from a decline in energy intensity and carbon intensity in the economic sectors. Among the different energy types, electricity has played a significant role in decreasing emissions because industries have reduced the consumption of electricity per output and the source of electricity generation has shifted to cleaner energies. These results imply that the Korean government should support strategies that reduce energy intensity and carbon intensity in the future to reduce CO2 emissions and maintain sustainable development

Predictive Abilities of Inflation Expectations and Implications on Monetary Policy in Korea

This paper examines the predictive abilities of various inflation expectation indicators for inflation in Korea. We conducted real-time out-of-sample forecasting experiments utilizing three inflation expectation indicators – the general public’s expectation, professional forecasters’ expectation, and break-even inflation (BEI). The results can be summarized as follows: (i) BEI is at least as useful as the other expectation indicators in forecasting inflation; (ii) regression-based models using industrial production, oil price, and exchange rate do not help out-of-sample inflation forecasting in general; (iii) the policy interest rate, in contrast, can significantly reduce the forecasting errors; and (iv) a one percent-point increase in the policy interest rate is estimated to suppress inflation for the subsequent 12 months by around one percent-point. These results suggest that monetary policy is effective for controlling inflation and a simple model using the policy interest rate and an inflation expectation indicator may be preferred for inflation forecasting.1

Long-Term Increases and Recent Slowdowns of CO2 Emissions in Korea

Korea is one of the fastest-growing CO2-emitting countries but has recently experienced a dramatic slowdown in emissions. The objective of the study is to examine the driving factors of long-term increases (1990–2015) and their slowdown (2012–2015) in emissions of Korea. This study uses an extended index decomposition analysis model that better fits Korea’s emission trends of the last 25 years by encompassing 19 energy end-use sectors (18 economic sectors and a household sector) and three energy types. The results show that emission increases in the long term (1990–2015) come from economic growth and population growth. However, improvements in energy intensity, carbon intensity, and economic structure offset large portions of CO2 emissions. The recent slowdown (2012–2015) mainly resulted from a decline in energy intensity and carbon intensity in the economic sectors. Among the different energy types, electricity has played a significant role in decreasing emissions because industries have reduced the consumption of electricity per output and the source of electricity generation has shifted to cleaner energies. These results imply that the Korean government should support strategies that reduce energy intensity and carbon intensity in the future to reduce CO2 emissions and maintain sustainable development.</jats:p

Attribution of Changes in Vietnam&rsquo;s Labor Productivity

This study examines the change in labor productivity in Vietnam by means of a Fisher index decomposition and attribution analysis. The results can be summarized as follows. First, the aggregate labor productivity is decomposed into pure labor productivity and structural change from 2007 to 2019. All of the aggregate labor productivity, pure labor productivity, structural change, and interaction terms have increased by 69.83%, 36.74%, 24.20%, and 8.89%, respectively. Second, the percentage change in labor productivity is attributed to 20 sub-industries by pure labor productivity and structural change. The sum of the multi-period attribution of pure labor productivity and structural change shows that the manufacturing industry positively dominates (15.84%) and plays a key role in economic development. The positive pure labor productivity and structural change in the manufacturing industry imply that the structural bonus hypothesis does hold in the industry. The findings also indicate that pure labor productivity, especially in the service industry, should be improved to sustain economic growth