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Effects of the Utilization of Non-Reciprocal Trade Preferences Offered by QUAD Countries on Economic Growth in Beneficiary Countries
Full text linkThe present article investigates empirically whether non-reciprocal trade preferences (NRTPs) offered by QUAD countries (Canada, the European Union, Japan, and the United States) to developing countries have helped to promote economic growth in the beneficiary countries. Two main blocks of NRTPs are considered here: Generalized System of Preferences (GSP) programs and other trade preferences programs. The analysis used a set of 90 beneficiary countries of NRTPs that are concurrently recipients of development aid over the period of 2002-2018. Using the two-step system generalized method of moments, the analysis indicated that while a higher degree of utilization of each of these two blocks of NRTPs has been associated with a high economic growth rate, development aid enhances this positive effect. This highlights the need for donors to support a development strategy based on the provision of both development aid and NRTPs if they are to help beneficiary countries to promote economic growth. Finally, when the positive economic growth effect of the utilization of NRTPs is higher, the result is a greater country’s share of exports (under preferential tariffs) to QUAD countries out of their total merchandise exports
Sectoral wage gaps and gender in rural India
No full textUsing detailed monthly household panel data from rural India, I analyze sectoral wage gaps for men and women. I show that the wage gap across the non-farm and farm sectors is much higher for women than for men. Relative to men, women also work less time in non-farm wage employment than in farm wage employment. Taken together, these findings suggest that constraints are preventing women from reallocating their time to more remunerative wage employment opportunities. Women are less likely to work outside of their own village in the non-farm sector, yet the wage gap is driven by higher caste and married women. These results are consistent with a lack of local non-farm employment opportunities interacting with barriers to labor mobility for women but not men.1
Investigating Effects of Customer Satisfaction, Awareness, Participation for e-CRM-Oriented Non-Profit Organization’s Public Sector Marketing : The Case of the Republic of Korea National Red Cross
No full text본 연구는 비영리기관의 공공 기관 디지털 마케팅 활동 및 CRM에 관한 실증 연구로 대한적십자사의 디지털 마케팅 활동 사례를 양적 및 질적 분석을 통해 검토하고, 마케팅 활동의 중요 요소인 웹사이트의 정보의 질, 최신성, 유용성, 심미적 요인, 참여도 및 인지도가 고객만족도에 유의한 영향을 미치는지를 분석했다. 양적 분석은 대한적십자사의 만족도 설문조사 데이터를 활용해, 다중회귀분석을 적용하여 가설을 검증했고, 질적 분석은 전문가 개별 심층 인터뷰로 분석했다. 본 연구의 결과로 공공기관 마케팅 활동에서 정보의 질, 최신성, 유용성, 심미적 요인, 참여도 및 인지도가 고객 만족도에 유의한 영향을 미치는 것을 확인했고, 효과의 크기는 인지도, 유용성, 심미적 요인, 정보의 질, 정보의 최신성, 참여도 순으로 나타났다. 본 연구는 영리 기업에 활용되고 있는 마케팅 활동이 비영리 기관에도 적용되며e-CRM의 응용이 공공기관의 마케팅 활동의 중요한 부분이며 이에 따른 시사점을 제시한다.2
Local and global experience curves for lumpy and granular energy technologies
No full textCurrent electricity generation systems have been dominated by lumpy energy technologies because the electricity they create has been cheaper than that generated from granular technologies. Accelerating the development and deployment of low-carbon technologies to mitigate climate change will require a better understanding of how lumpy and granular technology innovations work to reduce domestic and foreign technology costs. We estimated one-factor and two-factor experience curves to identify drivers and assess the relative importance of local and global learning experiences in Korea's climate change mitigation efforts between lumpy and granular energy technologies. The results suggest that granular technologies are likely to play a key role in mitigating climate change due to a rapid decline in its cost. Further tapping the local potential of cost reduction in granular technologies will require decreasing the soft costs of solar technologies and ramping up wind power plant installations. The results also suggest that knowledge spillover is relatively limited and slow for lumpy technologies, but frequent and fast for granular technologies. To maximize the spillover of global learning to local innovators, policy makers should improve the absorptive capacity of a country and strengthen the global network ties of local firms.1
Exhaustive or exhausting? Evidence on respondent fatigue in long surveys
No full textLiving standards measurement surveys require sustained attention for several hours. We quantify survey fatigue by randomizing the order of questions in 2–3 hour-long in-person surveys. An additional hour of survey time increases the probability that a respondent skips a question by 10%–64%. Because skips are more common, the total monetary value of aggregated categories such as assets or expenditures declines as the survey goes on, and this effect is sizeable for some categories: for example, an extra hour of survey time lowers food expenditures by 25%. We find similar effect sizes within phone surveys in which respondents were already familiar with questions, suggesting that cognitive burden may be a key driver of survey fatigue.1
Improving Estimates of Mean Welfare and Uncertainty in Developing Countries
No full textReliable estimates of economic welfare for small areas are valuable inputs into the design and evaluation of development policies. This paper compares the accuracy of point estimates and confidence intervals for small area estimates of wealth and poverty derived from four different prediction methods: linear mixed models, Cubist regression, extreme gradient boosting, and boosted regression forests. The evaluation draws samples from unit-level household census data from four developing countries, combines them with publicly and globally available geospatial indicators to generate small area estimates, and evaluates these estimates against aggregates calculated using the full census. Predictions of wealth are evaluated in four countries and poverty in one. All three machine learning methods outperform the traditional linear mixed model, with extreme gradient boosting and boosted regression forests generally outperforming the other alternatives. The proposed residual bootstrap procedure reliably estimates confidence intervals for the machine learning estimators, with estimated coverage rates across simulations falling between 94 and 97 percent. These results demonstrate that predictions obtained using tree-based gradient boosting with a random effect block bootstrap generate more accurate point and uncertainty estimates than prevailing methods for generating small area welfare estimates
Regulatory Sentiment and Economic Performance
Full text linkRegulatory sentiment refers to the market’s subjective evaluation of regulatory reform and is one of the most widely adopted indicators to those charged with implementing and diagnosing regulatory policies. The use of regulatory sentiment in advanced analysis has become universal, albeit it is often limited due to difficulties in articulating consistent and objective quantitative indicators that can meticulously reflect market sentiment overall. Thus, despite ample effort by scholars to read the economic impact of regulatory sentiment in the real economy, causal links are difficult to spot. To fill this gap in the literature, this study analyzes a regulatory sentiment index and economic performance indicators through a text analysis approach and by inspecting diverse tones in media articles. Using different stages of tests, the paper identifies a causal relationship between regulatory sentiment and actual economic activities as measured by private consumption, facility investment, construction investment, gross domestic investment, and employment. Additionally, as a result of analyzing one-unit impulse of regulatory perception, the initial impact on economic growth and private investment was found to be negligible; this was followed by a positive (+) response, after which it converged to zero. Construction investment showed a positive (+) response initially, which then rapidly changed to a negative (-) response and then converged to zero. Gross domestic investment as the initial effect was negligible after showing a positive (+) reaction. Unfortunately, the facility investment outcome was found to be insignificant in the impulse response test. Nevertheless, it can be concluded that it is necessary and important to increase the sensitivity to regulations to promote the economic effectiveness of regulatory reforms. Thus, instead of dealing with policies with the vague goal of merely improving regulatory sentiment, using regulatory sentiment as an indicator of major policies could be an effective approach
Sectoral Differences in the Relationship between Employment and Fertility among Married Females
No full text본 연구는 기혼여성의 경제활동과 총 자녀 수, 자녀 유무, 둘째아 여부 및 추가 출산 의향과의 관계를 직장 유형에 따른 차이를 중심으로 실증 분석하였다. 전국 출산력 및 가족 보건･복지 실태조사 2009~2018년 자료의 기혼여성 표본에 대한 포아송 모형, 이항 로지스틱 모형 및 성향점수 매칭 평균처리효과 모형 분석을 시행한 결과, 기혼여성의 취업, 특히 민간부문 및 중소기업 취업은 총 자녀 수와 통계적으로 유의한 부의 관계가 있었다. 공공부문 취업, 특히 정부기관 취업은 총 자녀 수와 둘째아 출산에 통계적으로 유의한 정의 관계가 있었다. 이러한 결과는 기혼여성의 취업과 출산과의 관계는 직장 유형에 따라 다르게 나타나며, 고용 안정성, 일･가정 양립 지원 등 근로조건의 개선과 사각지대 해소가 저출산 대응에 유효한 정책임을 시사한다.2
Spatial Pattern of Aid Allocation at the Regional Level: Evidence from 38 Sub-Saharan African Countries
Full text linkThis study aims to analyze the geographical patterns of aid in the 21st century for 38 countries in sub-Sahara Africa and to identify the spatial exclusion of aid at the regional level. We calculated the spatial exclusion level (SEL) of aid by comparing the multidimensional poverty index (MPI) and aid spend, considering different sectors; health, education, and water & sanitation. Geocoded data from International Aid Transparency Initiative (IATI) was utilized and the number of projects is roughly 250,000. We found that the regions with higher MPI received less aid, leading to high spatial exclusion levels (SEL). Then, we identified that regions with similar SELs tend to cluster. Also, aid concentrated in regions that have urban properties or high accessibility. This spatial inequality of aid has intensified over time. The findings emphasize the need to target the appropriate sector of aid in consideration of spatial exclusion and regional geography