Search results
1 – 4 of 4Changfei Nie, Haohui Wang and Yuan Feng
This paper aims to test the causal relationship between urban-biased policy and urban-rural income gap and further examine the moderating role of government intervention.
Abstract
Purpose
This paper aims to test the causal relationship between urban-biased policy and urban-rural income gap and further examine the moderating role of government intervention.
Design/methodology/approach
Based on the provincial Government Work Reports and the long-term policy practice of implementing the target responsibility system, the authors construct a unique indicator of urban-biased policy in China. Further, applying the panel data of 30 Chinese provinces in 2003–2018, the authors explore the causal relationship between urban-biased policy and urban-rural income gap.
Findings
The results show that urban-biased policy has contributed to the widen urban-rural income gap in China, which supports Lipton's urban-biased hypothesis. Further research shows that the stronger the government intervention, the bigger the role of urban-biased policy in widening urban-rural income gap.
Originality/value
On the one hand, this study not only investigates the direct effect of urban-biased policy on urban-rural income gap, but also examines the moderating effect from the perspective of government intervention, which helps to enrich the relevant studies of urban-biased theory. On the other hand, the authors' findings provide the latest empirical evidence for urban-biased policy to widen urban-rural income gap and presents a reference and warning for China and other developing countries about balancing the relationship between equity and efficiency during economic development.
Details
Keywords
Abebe Hambe Talema and Wubshet Berhanu Nigusie
The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in…
Abstract
Purpose
The purpose of this study is to analyze the horizontal expansion of Burayu Town between 1990 and 2020. The study typically acts as a baseline for integrated spatial planning in small- and medium-sized towns, which will help to plan sustainable utilization of land.
Design/methodology/approach
Landsat5-TM, Landsat7 ETM+, Landsat5 TM and Landsat8 OLI were used in the study, along with other auxiliary data. The LULC map classifications were generated using the Random Forest Package from the Comprehensive R Archive Network. Post-classification, spatial metrics, and per capita land consumption rate were used to understand the manner and rate of expansion of Burayu Town. Focus group discussions and key informant interviews were also used to validate land use classes through triangulation.
Findings
The study found that the built-up area was the most dynamic LULC category (85.1%) as it increased by over 4,000 ha between 1990 and 2020. Furthermore, population increase did not result in density increase as per capita land consumption increased from 0.024 to 0.040 during the same period.
Research limitations/implications
As a result of financial limitations, there were no high-resolution satellite images available, making it challenging to pinpoint the truth as it is on the ground. Including senior citizens in the study region allowed this study to overcome these restrictions and detect every type of land use and cover.
Practical implications
Data on urban growth are useful for planning land uses, estimating growth rates and advising the government on how best to use land. This can be achieved by monitoring and reviewing development plans using satellite imaging data and GIS tools.
Originality/value
The use of Random Forest for image classification and the employment of local knowledge to validate the accuracy of land cover classification is a novel approach to properly customize remote sensing applications.
Details
Keywords
This study aims to examine the effect of structural transformation on poverty alleviation in Sub-Saharan Africa (SSA) countries with a higher share of services as a percentage of…
Abstract
Purpose
This study aims to examine the effect of structural transformation on poverty alleviation in Sub-Saharan Africa (SSA) countries with a higher share of services as a percentage of gross domestic product (GDP). The study specifically focuses on the value-added share as a percentage of GDP in the agricultural, manufacturing, industrial, and service sectors using time series data from 1988 to 2019.
Design/methodology/approach
The study utilizes the autoregressive distributive lag (ARDL) bound test framework for estimation, based on the conclusions drawn from the augmented Dickey-Fuller and Phillips–Perron unit root tests, which provide evidence of a mixed order of integration.
Findings
The result reveals that agriculture value-added (AVA), manufacturing value-added (MVA), industrial value-added (IVA), and services value-added (SVA) have a positive and significant impact on poverty alleviation in both the short and long run. However, the agriculture sector is found to be more effective in reducing poverty compared to the other sectors examined in this study. Additionally, this study challenges the notion that SSA countries have undergone an immature structural transformation. Instead, it reveals a pattern of stagnant structural transformation, as indicated by the lack of growth in the industrial and manufacturing value-added shares of GDP.
Practical implications
To enhance productivity and reduce poverty, SSA economies should adopt a development strategy that prioritizes heavy manufacturing and industrial sectors, leading to a transition from the agricultural to the secondary and tertiary sectors.
Originality/value
The study contributes to the emerging literature on structural transformation by investigating which sector is more efficient in reducing poverty in SSA countries, using the value-added share as a percentage of GDP for agricultural, manufacturing, industrial, and service sectors. The study also aims to determine if SSA countries have experienced immature structural transformation due to the growing share in the service sector.
Details
Keywords
Bismark Amfo, Vincent Abankwah and Mohammed Tanko
This study investigated consumers' satisfaction with local rice attributes and willingness to pay (WTP) for improvement by internal migrants and natives in urban Ghana.
Abstract
Purpose
This study investigated consumers' satisfaction with local rice attributes and willingness to pay (WTP) for improvement by internal migrants and natives in urban Ghana.
Design/methodology/approach
Primary data was sourced from 304 urban consumers and ordered probit regression was employed.
Findings
Urban consumers had higher satisfaction with imported rice attributes than local rice. Consumers were unsatisfied with aroma, availability/accessibility, cleanliness, packaging, grain appearance, measurement standard, and taste of local rice. Moreover, 90% were willing to pay higher prices for local rice with improved attributes and WTP was higher among natives than migrants. Averagely, urban consumers are willing to pay 51% increase in market price of local rice if attributes were improved. Natives, males, educated, high-income, local rice consumption, shopping from supermarkets, trust in certification bodies, and dissatisfaction with local rice attributes boost WTP for improved local rice attributes.
Research limitations/implications
There is a great market potential for local rice with improved attributes. Thus, there should be an improvement in local rice attributes and sold at moderate price and in supermarkets.
Originality/value
We compared consumers' satisfaction and WTP for improved local rice attributes among internal migrants and natives in urban Ghana.
Details