scholarly journals Determinants of Urban Sprawl: A Panel Data Approach

2017 ◽  
Vol 4 (2) ◽  
pp. 25 ◽  
Author(s):  
Joseph S. DeSalvo ◽  
Qing Su
Keyword(s):  
Panel Data ◽  
Household Income ◽  
Fixed Effects ◽  
Transportation Cost ◽  
Urban Fringe ◽  
Intergovernmental Transfers ◽  
Land Rent ◽  
Urbanized Area ◽  
Spatial Size ◽  
The Impact

This paper applies fixed effects (within-groups) and between-groups estimations to panel data to test hypotheses of the monocentric urban model with urbanized area data for the period 1990–2010. The paper examines the impact of population, household income, transportation cost, and land rent at the urban fringe on urbanized area spatial size. The fixed effects regression finds that a 1- percent increase in population and a 1- percent decrease in travel cost causes an urbanized area to expand by 1.087 percent and 0.127 percent, respectively. The impact of household income is non-linear. The regression results from the between-groups estimation indicate that geographic and political factors help explain the spatial size differences across urbanized areas. The spatial size of an urbanized area is larger with a higher percentage of the urban fringe overlying aquifers, a higher percentage of local revenues from intergovernmental transfers, a higher percentage of urban fringe incorporated in 1980, and a lower elevation range in the urban fringe.

scholarly journals The impact of the Vietnam Bank for Social Policies preferential credit on household welfare in Vietnam: a panel data analysis

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
An Duong
Keyword(s):  
Panel Data ◽  
Household Income ◽  
Fixed Effects ◽  
Household Welfare ◽  
Social Policies ◽  
Content Type ◽  
Household Poverty ◽  
Poverty Status ◽  
Status Assessment ◽  
The Impact

PurposeThis study aims to examine the impact of the preferential credit (represented by loan volume and duration) provided by the Vietnam Bank for Social Policies on household welfare (represented by household income and consumption) in Ninh Binh province, Vietnam. It also identifies and ranks the barriers of accessing the credit.Design/methodology/approachThe study applies fixed-effects method to handle the panel data to examine the impact of the credit on poverty reduction. It also uses face-to-face interviews and group discussions to identify and rank the barriers of accessing to the credit.FindingsThe results show that the loan volume significantly helps improve household income, but does not help improve household consumption. For example, a 1% increase in the loan volume is associated with an increase of almost 0.69% in household income, significant at the 1% level. In addition, the loan duration does not help improve household welfare. The major barriers of accessing the credit include the time spent to get to the nearest bank branch and the transparency of household poverty status assessment.Research limitations/implicationsData are collected in three years, the number of the sample limits at 300 households. A few variables are not included in the models due to resource limitation for data collection or the nature of the study method.Practical implicationsThe Vietnam Bank for Social Policies preferential credit may need to increase the loan volume to significantly help improve household welfare, hence reduce poverty. In addition, barriers of accessing the credit such as bank coverage and the household poverty status assessment should be eliminated so that more households, including poor ones, can have a better access.Social implicationsThe Vietnam Bank for Social Policies preferential credit can help to improve household welfare, hence ease household poverty status. To help the credit reach more people, accessing barriers such as bank coverage and the household poverty status assessment should be eliminated.Originality/valueThis is the first study that has examined the impact of the Vietnam Bank for Social Policies preferential credit on household welfare and identified barriers of accessing the credit. The quantitative analysis uses a panel data set constructed from 300 face-to-face interviews with households located in one city and two districts in Ninh Binh province during 2016–2018 and applied the fixed-effects method to examine the impact of the credit on household welfare. The qualitative analysis uses in-depth interviews and group discussion with key persons and related parties to identify barriers of accessing the credit.

Assessing the Impact of the Factors in the Digital Transformation on the Regional Economic Growth

REGIONOLOGY ◽  
2021 ◽  
Vol 29 (3) ◽  
pp. 486-510
Author(s):  
Tatyana V. Mirolyubova ◽  
Marina V. Radionova
Keyword(s):  
Economic Growth ◽  
Panel Data ◽  
Fixed Effects ◽  
Digital Transformation ◽  
Regional Economic Growth ◽  
Regional Economic ◽  
The Russian Federation ◽  
Regional Product ◽  
The Impact ◽  
Regions Of Russia

Introduction. The scientific problem under consideration is of particular relevance due to the need to assess the impact of the factors in the digital transformation of the regional economy and in the economic growth on the economic development of the regions of the Russian Federation. Based on the research conducted, the article presents an econometric assessment of the dependence of the level of the gross regional product per capita in the regions of Russia on such factors as digital labor and digital capital. Materials and Methods. The authors analyzed panel data from the Federal State Statistics Service covering 87 regions of Russia for the period from 2010 to 2018. The research methodology is based on the use of the Cobb–Douglas production function, statistical and correlation data analysis, as well as on econometric methods for studying panel data. Results. To analyze the impact of the digital transformation of the economy on the regional economic growth of the regions of Russia, various models based on panel data have been considered, such as the pooled model, fixed effects models, random effects models, as well as time-varying effects models using dummy variables. Based on statistical criteria, the best model has been chosen and conclusions have been drawn about the nature of the impact of the digital transformation indicators on the gross regional product per capita in the regions of Russia. Discussion and Conclusion. The results of econometric modeling have demonstrated that digital factors in economic growth (digital labor, digital capital), along with common factors in economic growth (labor and capital), affect the regional economic growth. According to the regional data for the period from 2010 to 2018, the time fixed effects model has proved to be the best model of the impact of the factors in economic growth and digital transformation on the economic development of the regions of the Russian Federation. The research results can be used when developing a public policy aimed at stimulating the digital transformation of the regional economy.

scholarly journals Maternal Mortality in Ghana: Impact of the Fee-Free Delivery Policy and the National Health Insurance Scheme

2015 ◽  
Vol 4 (3) ◽  
pp. 232
Author(s):  
Seidu Sofo ◽  
Emmanuel Thompson
Keyword(s):  
Health Insurance ◽  
Panel Data ◽  
Maternal Mortality ◽  
National Health Insurance ◽  
National Health ◽  
Data Model ◽  
Fixed Effects ◽  
Panel Data Model ◽  
Skilled Delivery ◽  
The Impact

<p>Maternal mortality (MMR) is the second largest cause of female deaths in Ghana. Yet, many households cannot afford the cost of skilled delivery The study utilized the Panel Data Model to examine the impact of the fee-free delivery (FDP) and the National Health Insurance Policy (NIP) exemptions on MMR in Ghana. The Demographic and Health Survey reports on Ghana from 2002 to 2009 served as the main data source. Data were analyzed using Panel data model with within group fixed effects estimator. MMR declined significantly over the period studied. Both FDP and NIP positively impacted MMR at a 5% level of significance. In addition, skilled delivery was a significant predictor of MMR. Stakeholders would do well to ensure NIP is adequately funded in order to sustain the decline in MMR.</p><p> </p><p><strong><br /></strong></p>

Estimating the Impact of Avian Flu on International Tourism Demand Using Panel Data

2009 ◽  
Vol 15 (3) ◽  
pp. 501-511 ◽  
Author(s):  
Hsiao-I Kuo ◽  
Chia-Lin Chang ◽  
Bing-Wen Huang ◽  
Chi-Chung Chen ◽  
Michael McAleer
Keyword(s):  
Panel Data ◽  
Pandemic Influenza ◽  
Fixed Effects ◽  
Data Models ◽  
International Tourism ◽  
Panel Data Models ◽  
Tourism Demand ◽  
Avian Flu ◽  
Potential Risks ◽  
The Impact

This paper investigates the impacts of avian flu on global and Asian tourism using panel data procedures. Both static and dynamic fixed effects panel data models are adopted to estimate the impacts of this infectious disease. The empirical results from static and dynamic fixed effects panel data models are consistent and indicate that the number of affected poultry outbreaks has significant impacts on the international tourism of global and Asian affected countries. The high mortality rate among humans, the potential of a global flu pandemic and some media frenzy with hype and speculation might adversely affect the images of these infected destinations as a safe tourist destination. Moreover, it was found that the average damage to Asian tourism was more serious, which might have been induced by an ineffective suppression in numerous Asian infected countries. In addition, Asia was the earliest affected region and the area infected most seriously by avian flu, both in humans and in poultry. Since the potential risks and damage arising from avian flu and the subsequent pandemic influenza are much greater than for previous diseases, the need to take necessary precautions in the event of an outbreak of avian flu and pandemic influenza warrants further attention and action in modelling and managing international tourism demand and risk.

Globalization and health: An empirical investigation

2019 ◽  
Vol 19 (3) ◽  
pp. 207-224 ◽  
Author(s):  
Vishalkumar J Jani ◽  
Nisarg A Joshi ◽  
Dhyani J Mehta
Keyword(s):  
Health Status ◽  
Panel Data ◽  
Fixed Effects ◽  
Panel Data Analysis ◽  
Health Indicators ◽  
Developed Countries ◽  
Social Dimension ◽  
Three Dimensions ◽  
Infant Mortality Rate ◽  
The Impact

This article empirically examines the impact of globalization on the health status of countries by using panel data. Unlike previous studies, it has attempted to use three different dimensions of globalization and estimate their impact on health status measured by infant mortality rate and life expectancy. It also introduces an initial level of development status as an explanatory variable and found that it has an important role. The fixed effects panel data analysis shows that globalization has a positive impact on the health indicators. Out of the three dimensions of globalization, namely, economic, social and political, the first one has the highest influence on health for the less developed countries. However, as one moves up the ladder of development, social dimension becomes more important. Moreover, the pace of improvement in health indicators is faster in developed countries, indicating a divergence between the developed and the underdeveloped world.

scholarly journals FORECASTING MONEY DEMAND WITH THE INCLUSION OF FINANCIAL INNOVATION FOR THE ASSOCIATION OF SOUTHEAST ASIAN NATIONS: EVIDENCE FROM PANEL DATA ANALYSIS

2019 ◽  
Vol 1 (1) ◽  
pp. 59-74
Author(s):  
Payam Mohammad Aliha ◽  
Tamat Sarmidi ◽  
Fathin Faizah Said
Keyword(s):  
Time Series ◽  
Panel Data ◽  
Random Effects ◽  
Money Demand ◽  
Fixed Effects ◽  
Random Effects Model ◽  
Fixed Effects Model ◽  
Demand For Money ◽  
Financial Innovations ◽  
The Impact

This paper investigates the impact of financial innovations on the demand for money using a dynamic panel data for 10 ASEAN member states from 2004 to 2012 and attempt to forecast the demand for money during 2013 – 2016 to compare between forecasting performance of the fixed effects model with that of random effects model and also to compare the forecasting accuracy of dynamic forecasting and static forecasting obtained from these two models. An autoregressive model by definition is when a value from a time series is regressed on previous values from that same time series. There are two types of forecasting namely dynamic forecast and static forecast. “Dynamic forecast will take previously forecasted values while static forecast will take actual values to make next step forecast. Panel effects models assist in controlling for unobserved heterogeneity when this heterogeneity is constant over time and correlated (fixed effects) or uncorrelated (random effects) with independent variables. Hausman test indicates that the random-effects model is appropriate. We use the conventional money demand that is enriched with the number of automated teller machines (ATM) to proxy for the effect of financial innovations on money demand. By comparing the magnitude of “Root Mean Squared Error” (RMSE) as a benchmark for the two forecasts (0.1164 for dynamic forecast versus 0.0635 for static forecast) we simply find out that static forecast is superior to dynamic forecast meaning that static forecast provides more accurate forecast compared to a dynamic forecast for the fixed-effects model. Therefore, we conclude the static forecast on the basis of the random-effects model provides the most accurate forecasting. The estimation result of the chosen random-effects regression also indicates the estimated coefficient of ATM is not significant meaning that ATM does not impact money demand in ASEAN countries.

How the peer-to-peer market for tourist accommodation has responded to COVID-19

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Beatriz Benítez-Aurioles
Keyword(s):  
Panel Data ◽  
Fixed Effects ◽  
Design Methodology ◽  
Peer To Peer ◽  
Content Type ◽  
Public Managers ◽  
Before And After ◽  
Tourist Accommodation ◽  
The Impact ◽  
Practical Implications

Purpose This study aims to analyze the COVID-19 pandemic’s impact on the peer-to-peer (p2p) market for tourist accommodation. Design/methodology/approach Using monthly panel data from Airbnb listings in 22 cities worldwide, the authors run a differences-in-differences analysis comparing the period of February–October 2020 to the previous year. Findings Besides a decline in accommodation supply, the pandemic made prices and demand fall in all cities significantly, after controlling for room characteristics, host traits, booking policies and individual fixed effects. There is also evidence of an alteration of the influence on prices of certain variables such as superhost and instant booking. Research limitations/implications The main limitations are related to the reference spatial and temporal environment. Besides, the samples are limited to listings that stayed before and after the pandemic; therefore, it is possible that the real effect on review growth and/or prices is actually more negative. Practical implications The analysis performed shows a scenario that represents an opportunity for public managers to test more imaginative regulations that overcome the limitations of those implemented so far. Likewise, hosts who aspire to make their accommodations profitable must adapt to the conditions imposed by the economic environment of the cities in which they operate. Originality/value This is the first study to econometrically estimate the impact of COVID-19 on prices in the p2p market for tourist accommodation in a set of cities worldwide.

scholarly journals The Impacts of Charter Schools on Student Achievement: Evidence from North Carolina

2006 ◽  
Vol 1 (1) ◽  
pp. 50-90 ◽  
Author(s):  
Robert Bifulco ◽  
Helen F. Ladd
Keyword(s):  
North Carolina ◽  
Public Schools ◽  
Panel Data ◽  
Charter Schools ◽  
Fixed Effects ◽  
Data Set ◽  
Achievement Gains ◽  
Traditional Public Schools ◽  
Negative Effect ◽  
The Impact

Using an individual panel data set to control for student fixed effects, we estimate the impact of charter schools on students in charter schools and in nearby traditional public schools. We find that students make considerably smaller achievement gains in charter schools than they would have in public schools. The large negative estimates of the effects of attending a charter school are neither substantially biased, nor substantially offset, by positive impacts of charter schools on traditional public schools. Finally, we find suggestive evidence that about 30 percent of the negative effect of charter schools is attributable to high rates of student turnover.

Implications of less tail end water on livelihoods of small farmers in Pakistan

2017 ◽  
Vol 46 (1) ◽  
pp. 36-43 ◽  
Author(s):  
Akhter Ali ◽  
Dil Bahadur Rahut ◽  
Muhammad Imtiaz
Keyword(s):  
Water Availability ◽  
Water Scarcity ◽  
Household Income ◽  
Water Source ◽  
Land Rent ◽  
Absolute Deviation ◽  
Canal Irrigation ◽  
Using Data ◽  
The Impact ◽  
Poverty Levels

In Pakistan, about 80% of the cropped area is irrigated using canal irrigation, and water availability is closely linked to the location of the farm. Using data collected from 950 farmers through a field survey covering four provinces (Punjab, Sindh, Khyber Pakhtunkhwa and Balochistan), this study aimed to assess the impact of location, that is, ‘head’ versus ‘tail’ on water availability and its impact on crop yield, household income, food security and poverty levels. The censored least absolute deviation was used to estimate farmer participation in water markets, and the propensity score matching was used to assess impacts on yield of wheat and rice, household income and poverty levels as well as land rent and water scarcity. The results show that farmers situated at the head of the water source have higher wheat and rice yields in the range of 2–3 maunds per acre. Household income levels are higher in the range of PKR 8455–14,673, and poverty levels are lower (+3% to 5%). The land rent at the head is higher compared to the tail while water scarcity is also less at the head. The study indicated that farmers’ status plays a major role in land location and access to irrigation water.

scholarly journals The Impact of Retirement on Happiness and Loneliness in Poland—Evidence from Panel Data

2021 ◽  
Vol 18 (18) ◽  
pp. 9875
Author(s):  
Anita Abramowska-Kmon ◽  
Wojciech Łątkowski
Keyword(s):  
Quality Of Life ◽  
Panel Data ◽  
Fixed Effects ◽  
Logistic Models ◽  
Subjective Quality ◽  
Subjective Quality Of Life ◽  
Bridge Employment ◽  
The Social ◽  
The Impact

This paper examines the impact of retirement on people’s subjective quality of life, as expressed by their levels of happiness and loneliness, in Poland. We analysed five waves of the Social Diagnosis panel survey conducted between 2007 and 2015. To account for unobserved individual heterogeneity, we employed fixed effects ordered logit models and fixed effect logistic models for the panel data. We found that the respondents’ happiness levels did not change after they retired, and that the introduction of interactions between retirement and employment did not alter these findings. However, the results of the loneliness model showed that the probability of being lonely increased among males after retirement. Second, the outcomes of interactions between retirement and employment suggested that not working after retirement increased the likelihood of being lonely among men, whereas engaging in bridge employment decreased the chances of being lonely among men. These findings may indicate that combining retirement with employment may be a source of social interaction, which can provide protection against loneliness, and which may, in turn, be positively related to other factors (i.e., subjective quality of life, health status, and mortality).

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