The impact of higher speed limits on the frequency and severity of freeway crashes: Accounting for temporal shifts and unobserved heterogeneity

2021 ◽  
pp. 100205
Author(s):  
Nawaf Alnawmasi ◽  
Fred Mannering
Keyword(s):  
Unobserved Heterogeneity ◽  
Speed Limits ◽  
The Impact ◽  
Temporal Shifts

The Impact of ICT Investment on Establishment Productivity

2003 ◽  
Vol 184 ◽  
pp. 99-110 ◽  
Author(s):  
Thomas Zwick
Keyword(s):  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Data Set ◽  
Omitted Variable Bias ◽  
Lagged Effects ◽  
Variable Bias ◽  
Employee Characteristics ◽  
The Impact ◽  
Establishment Panel Data

This paper finds substantial effects of ICT investments on productivity for a large and representative German establishment panel data set. In contrast to the bulk of the literature also establishments without ICT capital are included and lagged effects of ICT investments are analysed. In addition, a broad range of establishment and employee characteristics are taken account of in order to avoid omitted variable bias. It is shown that taking into account unobserved heterogeneity of the establishments and endogeneity of ICT investments increases the estimated lagged productivity impact of ICT investments.

Emissions Impact of Eliminating National Speed Limits: One Year Later

1997 ◽  
Vol 1587 (1) ◽  
pp. 113-120
Author(s):  
Maureen A. Mullen ◽  
James H. Wilson ◽  
Laura Gottsman ◽  
Robert B. Noland ◽  
William L. Schroeer
Keyword(s):  
Maximum Speed ◽  
Speed Limit ◽  
Oxides Of Nitrogen ◽  
Speed Limits ◽  
The Past ◽  
Volatile Organic ◽  
National Highway ◽  
One Year ◽  
The Impact ◽  
Highway System

The National Highway System (NHS) bill passed by Congress in November 1995 eliminated the national maximum speed limit. It has allowed states to set their own speed limits, which many have changed during the past year. This analysis examines the impact of speed limit changes 1 year after passage of the NHS. Oxides of nitrogen (NOx), carbon monoxide, and volatile organic compounds are analyzed and are found to have increased nationwide by up to 6, 7, and 2 percent, respectively. Much of the increase has occurred in western states, which generally have increased vehicle speeds more than in eastern and midwestern states. For example, in Texas NOx emissions are estimated to have increased by 35 percent due to large increases in highway and arterial speed limits.

Revenue management systems and hotel performance in the economic downturn

2016 ◽  
Vol 28 (4) ◽  
pp. 658-680 ◽  
Author(s):  
Bienvenido Ortega
Keyword(s):  
Revenue Management ◽  
Unobserved Heterogeneity ◽  
Labour Productivity ◽  
Economic Conditions ◽  
Economic Downturn ◽  
Content Type ◽  
Hotel Performance ◽  
Context Specific ◽  
The Impact

Purpose The purpose of this paper is to analyse whether hotels that use a revenue management system (RMS) outperform non-RMS-users in a context of decreasing demand. Design/methodology/approach A database of chain hotels with a rating of three or more stars was used to estimate MANOVA and ANOVA models to analyse the role of RMSs in hotel performance. Findings In a context of strong competition in prices and surplus capacity, the findings suggest that RMSs have been more effective in improving occupancy than in achieving higher rates. Also, the use of RMSs did not have a significant impact on hotel labour productivity. Research limitations/implications Managers may believe that they have adopted an RMS when, in fact, they have not fully done so. In addition, establishment-level unobserved heterogeneity, such as the quality of management or unobserved quality of service, cannot be fully controlled because of the nature of the data used. The main implication of this paper is that the potential of RMSs as revenue enhancer might be influenced by unstable market and economic conditions. However, the absence of significant effects on RevPAR performance might be also the result of firms’ adopting inadequate RM strategies. Further research could investigate whether the findings are context-specific or whether firms are failing to implement effective RMSs for other reasons. Originality/value The approach used in this paper is new to the literature, given that it uses statistical methods to analyse the impact of implementing an RMS on hotel performance under specific economic conditions and using alternative indicators.

scholarly journals The Impact of Agricultural Technologies on Poverty and Vulnerability of Smallholders in Ethiopia: A Panel Data Analysis

2020 ◽  
Vol 147 (2) ◽  
pp. 517-544 ◽  
Author(s):  
Wubneshe Dessalegn Biru ◽  
Manfred Zeller ◽  
Tim K. Loos
Keyword(s):  
Panel Data ◽  
Unobserved Heterogeneity ◽  
Panel Data Analysis ◽  
Probit Model ◽  
Special Focus ◽  
Switching Regression ◽  
Agricultural Technologies ◽  
Adoption Decision ◽  
Vulnerable Households ◽  
The Impact

AbstractMany studies evaluating the impact of adoption on welfare focused on adoption of a single technology giving little attention on the complementarity/substitutability among agricultural technologies. Yet, smallholders commonly adopt several complementary technologies at a time and their adoption decision is best characterized by multivariate models. This paper, therefore, examines the impact of multiple complementary technologies adoption on consumption, poverty and vulnerability of smallholders in Ethiopia. The study used a balanced panel data obtained from a survey of 390 farm households collected in 2012, 2014 and 2016. A two stage multinomial endogenous switching regression model combined with the Mundlak approach and balanced panel data is employed to account for unobserved heterogeneity for the adoption decision and differences in household and farm characteristics. An ordered probit model is used to analyze the impact on poverty and vulnerability. We find that the adoption of improved technologies increases consumption expenditure significantly and the greatest impact is attained when farmers combine multiple complementary technologies. Similarly, the likelihood of households to remain poor or vulnerable decreased with the adoption of different complementary technologies. We therefore conclude that the adoption of multiple complementary technologies has substantial dynamic benefits that improve the welfare of smallholders in the study area, and given the observed low level of adoption rates, we suggest that much more intervention is warranted, with a special focus on poorer and vulnerable households, to ensure smallholders get support to improve their input use.

The Impact of Schooling Intensity on Student Learning: Evidence from a Quasi-Experiment

2019 ◽  
Vol 14 (4) ◽  
pp. 679-701
Author(s):  
Vincenzo Andrietti ◽  
Xuejuan Su
Keyword(s):  
Student Learning ◽  
Test Scores ◽  
International Student ◽  
Unobserved Heterogeneity ◽  
Student Assessment ◽  
Immigrant Parents ◽  
High Performing ◽  
International Student Assessment ◽  
Time Required ◽  
The Impact

This paper uses a quasi-natural policy experiment in Germany, the G8 reform, to examine the impact of schooling intensity on student learning. The G8 reform compresses secondary school for academic-track students from nine to eight years, while holding fixed the overall academic content and total instruction time required for graduation, resulting in a higher schooling intensity per grade. Using German extension of the Programme for International Student Assessment data, we find that this reform improves test scores on average, but the effect differs across subgroups of students. The reform effect is larger for girls than for boys, for students with German-born parents than for those with immigrant parents, and for students having more books at home. The heterogeneous reform effects cannot be explained by changes in observed channels. Instead, quantile regression results suggest that unobserved heterogeneity plays an important role: Whereas high-performing students significantly improve their test scores, the lowest-performing students hardly improve at all after the reform. We interpret the unobserved heterogeneity as reflecting students’ capability to cope with the increase in schooling intensity.

Labor income risk and households’ risky asset holdings

2016 ◽  
Vol 33 (2) ◽  
pp. 262-280 ◽  
Author(s):  
Gideon Becker ◽  
Thomas Dimpfl
Keyword(s):  
Unobserved Heterogeneity ◽  
Investment Decision ◽  
Labor Income ◽  
Income Risk ◽  
Cross Sectional ◽  
Financial Situation ◽  
Content Type ◽  
Labor Income Risk ◽  
Cross Sectional Dimension ◽  
The Impact

Purpose Financial theory suggests that with increasing labor income risk, the reluctance of households to hold stocks increases. Therefore, this paper aims to investigate the determinants of a household’s decision on whether to invest in risky financial assets. Design/methodology/approach Income risk is measured as the observed variation of household income over a five-year period. The authors use both the time and the cross-sectional dimension of the German socio-economic panel to control for unobserved heterogeneity. Findings The authors find that indeed higher variation, i.e. higher income risk, reduces the propensity to invest in risky assets. However, when controlling for household heterogeneity, as well as subjective measures of a household’s financial situation (income satisfaction, worries about financial situation), the impact of observed labor income variation vanishes. It is therefore concluded that in particular the perception of investment risk and of the riskiness of the environment determines the investment decision to a great extent. Originality/value The paper contributes to a better understanding of a household’s investment decision-making process. To the best of the authors’ knowledge, it is the first to fully exploit the panel structure of the data to control for unobserved heterogeneity which leads to novel conclusions with respect to the effect of labor income.

scholarly journals The Impact of Lagging-Region Status on District Poverty in Indonesia

2016 ◽  
Vol 62 (1) ◽  
pp. 30
Author(s):  
Rus’an Nasrudin
Keyword(s):  
Panel Data ◽  
Propensity Score ◽  
Propensity Score Matching ◽  
Selection Bias ◽  
Unobserved Heterogeneity ◽  
Poverty Rate ◽  
Fixed Effect ◽  
Omitted Variable Bias ◽  
Variable Bias ◽  
The Impact

Reducing subnational imbalances of development progress is unquestionable policy for heterogeneous Indonesia. This paper examines the impact of policy that assigns a lagging-region status namely status daerah tertinggal (DT) on poverty rate and poverty gap among districts in Indonesia in the two period of SBY presidency. The panel data fixed effect combined with propensity score matching is used to tackle the selection bias due to the nature of the policy, unobserved heterogeneity and omitted variable bias. The results show that the lagging-region status that was aimed to mainstream central and district’s budget toward lagging regions statistically significant reduces poverty rate and poverty gap in the period. The DT status, on average is associated with 0.75 percentage point of reduction in the poverty rate and 7% reduction in the poverty gap index. AbstrakMenurunkan ketimpangan antar-daerah adalah sebuah agenda kebijakan yang niscaya untuk Indonesia yang majemuk dalam kemajuan ekonomi. Artikel ini berusaha mengukur dampak dari sebuah kebijakan penetapan daerah tertinggal terhadap dua ukuran kemiskinan, yaitu tingkat kemiskinan dan kedalaman kemiskinan pada dua periode masa jabatan Presiden SBY. Metode yang dipergunakan adalah panel data fixed-effect dikombinasikan dengan propensity score matching untuk mengatasi permasalah endogen pada variabel utama yaitu bias dalam seleksi terhadap kebijakan, keragaman daerah yang tidak dapat diukur, dan potensi bias karena ketiadaan variabel-variabel yang berpengaruh terhadap dua ukuran kemiskinan. Hasil pendugaan regresi tersebut menunjukkan bahwa penetapan daerah tertinggal yang ditujukan untuk mengarusutamakan dana pembangunan secara statistik signifikan dan menyebabkan penurunan tingkat kemiskinan dan kedalaman kemiskinan di masa tersebut. Daerah tertinggal secara rata-rata memiliki tingkat kemiskinan lebih rendah sebesar 0.75 (persentase) dan memiliki indeks kedalaman kemiskinan 7% lebih rendah.Kata kunci: Daerah Tertinggal; Kemiskinan; IndonesiaJEL classifications: I32, P48

scholarly journals Why do people continue to live near polluted sites? Empirical evidence from Southwestern Europe

2021 ◽  
Author(s):  
Pierre Levasseur ◽  
Katrin Erdlenbruch ◽  
Christelle Gramaglia
Keyword(s):  
Affordable Housing ◽  
Unobserved Heterogeneity ◽  
Economic Status ◽  
Location Choices ◽  
Middle Income ◽  
Original Dataset ◽  
The Us ◽  
Residence Location ◽  
Pollution Exposure ◽  
The Impact

Abstract Poverty is a major determinant for pollution exposure, according to the US location choice literature. In this paper, we assess the impact of socio-economic status on location choices in the European context. Our analysis relies on an original dataset of 1194 households living in polluted and non-polluted areas in three European countries: Spain, Portugal and France. We use instrumental variables strategies to identify the socioeconomic causes of location choices. We show that low education, wealth and income are main reasons for living in polluted areas. We provide several robustness checks testing for the exogeneity of selected instruments. We observe that unobserved heterogeneity tends to understate the impact of socioeconomic status on residence location. Interestingly, we highlight that an important proportion of intermediate social groups (especially young couples) are living in polluted areas, probably because of place attachment and affordable housing facilities. Similarly, we show that middle-income households have lower move-out intentions than other income groups. These latter results contrast the linear vision of environmental inequalities found in the US.

scholarly journals A Comparison of Mean-Based and Quantile Regression Methods for Analyzing Self-Report Dietary Intake Data

2019 ◽  
Vol 2019 ◽  
pp. 1-5
Author(s):  
Michelle L. Vidoni ◽  
Belinda M. Reininger ◽  
MinJae Lee
Keyword(s):  
Health Behavior ◽  
Dietary Intake ◽  
Quantile Regression ◽  
Unobserved Heterogeneity ◽  
Study Groups ◽  
Behavior Intervention ◽  
Self Report ◽  
Unhealthy Eating ◽  
Health Behavior Intervention ◽  
The Impact

In mean-based approaches to dietary data analysis, it is possible for potentially important associations at the tails of the intake distribution, where inadequacy or excess is greatest, to be obscured due to unobserved heterogeneity. Participants in the upper or lower tails of dietary intake data will potentially have the greatest change in their behavior when presented with a health behavior intervention; thus, alternative statistical methods to modeling these relationships are needed to fully describe the impact of the intervention. Using data from Tu Salud ¡Si Cuenta! (Your Health Matters!) at Home Intervention, we aimed to compare traditional mean-based regression to quantile regression for describing the impact of a health behavior intervention on healthy and unhealthy eating indices. The mean-based regression model identified no differences in dietary intake between intervention and standard care groups. In contrast, the quantile regression indicated a nonconstant relationship between the unhealthy eating index and study groups at the upper tail of the unhealthy eating index distribution. The traditional mean-based linear regression was unable to fully describe the intervention effect on healthy and unhealthy eating, resulting in a limited understanding of the association.

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