Gasoline and Travel Demand Models Using Time Series and Cross-Section Data from United States

1996 ◽  
Vol 1558 (1) ◽  
pp. 83-89 ◽  
Author(s):  
Paul Schimek
Keyword(s):  
United States ◽  
Time Series ◽  
Travel Demand ◽  
Time Series Data ◽  
Fuel Efficiency ◽  
Rebound Effect ◽  
The United States ◽  
Series Data ◽  
Price And Income Elasticities ◽  
Demand Models

The price and income elasticities of highway gasoline and automobile travel demand are useful for forecasting gasoline tax revenues and highway investment needs and evaluating policies to reduce automobile use, improve fuel efficiency, or reduce greenhouse gas emissions. Gasoline and travel demand elasticities are calculated using 1950 to 1994 time series data for the United States and 1988 to 1992 pooled data for states of the United States. Gasoline demand was found to be price inelastic in the short run, but in the long run, it was found to be —0.7. Even in the United States, gasoline price has a significant impact on gasoline use. The response to price changes is divided among driving, fuel efficiency, and the size of the vehicle stock, although the latter is the smallest. The Corporate Average Fuel Economy (CAFE) program was found to be associated with an average 1 percent annual decline in per capita fuel consumption. The elasticity of driving with respect to fuel efficiency— the rebound effect—was found to be —0.3, confirming previous results. The state-level data produce inconclusive results; it is hypothesized that this is the result of the confounding effect of CAFE.

Age, Generations, and Participation

2017 ◽  
Author(s):  
Russell J. Dalton
Keyword(s):  
United States ◽  
Time Series ◽  
Life Cycle ◽  
Millennial Generation ◽  
Time Series Data ◽  
Direct Action ◽  
The United States ◽  
Series Data ◽  
Online Participation ◽  
Modes Of Action

Political scientists debate whether the Millennial generation is disengaging from politics in contemporary democracies. The ISSP surveys show that the generational decline in participation is largely limited to voting and other forms of partisan activity. At the same time, younger citizens are often more engaged in non-electoral activities, such as direct action, protest, and online participation. Time-series data for the United States disentangles the effects of life-cycle changes and generations. More recent generations display a clear decline in voting across the 1967–2014 period. In contrast, life-cycle increases in participation are more common for non-electoral activity. Both factors influence participation but in contrasting ways for different modes of action.

Crime and the Use of Prisons in the United States: A Time Series Analysis

1981 ◽  
Vol 27 (2) ◽  
pp. 206-212 ◽  
Author(s):  
Lee H. Bowker
Keyword(s):  
United States ◽  
Time Series ◽  
Time Series Analysis ◽  
Recent Article ◽  
Positive Relationship ◽  
Time Series Data ◽  
The United States ◽  
Series Data ◽  
Cross Sectional ◽  
Correctional Policy

A recent article by David Biles reported a positive relationship between crime and imprisonment, using cross-sectional data from the United States, Australia, and Canada. This article extends his analysis, using two sets of time series data on crime and imprisonment rates for the United States as a whole. The unlagged correlations between the crime and imprisonment rates for 1941-57 and 1958-78 are not statistically signifi cant, but one of six lagged correlations from 1958-78 is significant, as are four of six from 1941-57. The inconsistency in correlation provides little guidance for the development of correctional policy. Considering these findings, William Nagel's support for a moratorium on prison construction takes on the color of a reasonable, and perhaps even conservative, reading of available policy and management data rather than a radical proposition for change.

scholarly journals A Multiscale Spatial Dataset for Policy-Driven Land Developability across the United States, 2001–2011

2020 ◽  
Author(s):  
Hung Chak Ho ◽  
Guangqing Chi
Keyword(s):  
United States ◽  
Time Series ◽  
Population Dynamics ◽  
Health Risks ◽  
Time Series Data ◽  
Land Development ◽  
The United States ◽  
Land Policy ◽  
Series Data ◽  
Spatial Dataset

Abstract. Land vulnerability and development can be restricted by both land policy and geophysical limits. Land vulnerability and development cannot be simply quantified by land cover/use change, because growth related to population dynamics is not horizontal. Particularly, time-series data with a higher flexibility considering the ability of land to be developed should be used to identify areas of spatiotemporal change. By considering the policy aspects of land development, this approach will allow one to further identify the lands facing population stress, socioeconomic burdens, and health risks. Here the concept of “land developability” is expanded to include policy-driven factors and land vulnerability to better reconcile developability with socio-environmental justice. The first phrase of policy-driven land developability mapping is implemented in estimating land information across the contiguous United States in 2001, 2006, and 2011. Multiscale data products for state-, county- and census-tract-levels are provided from this estimation. The extension of this approach can be applied to other countries with modifications for their specific scenarios. The data generated from this work are available at https://doi.org/10.7910/DVN/AMZMWH (Chi and Ho, 2019).

scholarly journals Phenological Classification of the United States: A Geographic Framework for Extending Multi-Sensor Time-Series Data

2010 ◽  
Vol 2 (2) ◽  
pp. 526-544 ◽  
Author(s):  
Yingxin Gu ◽  
Jesslyn Brown ◽  
Tomoaki Miura ◽  
Willem J. Van Leeuwen ◽  
Bradley Reed
Keyword(s):  
United States ◽  
Time Series ◽  
Time Series Data ◽  
The United States ◽  
Series Data

Corn and Soybean Mapping in the United States Using MODIS Time-Series Data Sets

2007 ◽  
Vol 99 (6) ◽  
pp. 1654-1664 ◽  
Author(s):  
Jiyul Chang ◽  
Matthew C. Hansen ◽  
Kyle Pittman ◽  
Mark Carroll ◽  
Charlene DiMiceli
Keyword(s):  
United States ◽  
Time Series ◽  
Time Series Data ◽  
The United States ◽  
Series Data ◽  
Data Sets

Faktor-Faktor Yang Mempengaruhi Nilai Tukar Dollar Amerika Serikat Terhadap Rupiah Tahun 2000–2013

2017 ◽  
Vol 1 (2) ◽  
pp. 177-191
Author(s):  
Rizki Rahma Kusumadewi ◽  
Wahyu Widayat
Keyword(s):  
Time Series ◽  
Exchange Rate ◽  
Money Supply ◽  
Time Series Data ◽  
The United States ◽  
Economic Conditions ◽  
Series Data ◽  
Arch Model ◽  
United States Dollar ◽  
The Exchange Rate

Exchange rate is one tool to measure a country’s economic conditions. The growth of a stable currency value indicates that the country has a relatively good economic conditions or stable. This study has the purpose to analyze the factors that affect the exchange rate of the Indonesian Rupiah against the United States Dollar in the period of 2000-2013. The data used in this study is a secondary data which are time series data, made up of exports, imports, inflation, the BI rate, Gross Domestic Product (GDP), and the money supply (M1) in the quarter base, from first quarter on 2000 to fourth quarter on 2013. Regression model time series data used the ARCH-GARCH with ARCH model selection indicates that the variables that significantly influence the exchange rate are exports, inflation, the central bank rate and the money supply (M1). Whereas import and GDP did not give any influence.

scholarly journals Determinants of Exports of Pakistan: A Country-wise Disaggregated Analysis.

2011 ◽  
Vol 50 (4II) ◽  
pp. 715-732 ◽  
Author(s):  
Naseeb Zada ◽  
Malik Muhammad ◽  
Khan Bahadar
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Export Performance ◽  
Small Samples ◽  
Series Data ◽  
Supply Side ◽  
Empirical Bayesian ◽  
Demand And Supply ◽  
Price And Income Elasticities ◽  
Trade Partners

Given the importance of international trade and export performance in economic growth, this study attempts to examine the determinants of exports of Pakistan, using a time series data over the period 1975-2008. A simultaneous equation approach is followed and the demand and supply side equations are specified with appropriate variables. This is a country-wise disaggregated analysis of Pakistan versus its trade partners and the estimation strategy is based on two approaches. First we employ the Generalised Methods of Moments (GMM), which is followed by the Empirical Bayesian technique to get consistent estimates. The GMM technique is believed to be efficient for time series data provided the sample size is sufficiently large. In case of small samples, the estimates might not be precise and might appear with unbelievable sign and insignificant magnitudes. To avoid the sample bias and other problems, we employ the Empirical Bayesian technique which provides much precise estimates. The factual results obtained via the GMM technique are a little bit mixed, although most of the coefficients are found to be statistically significant and carry their expected signs. In order to compare and validate these results, the Empirical Bayesian technique is employed. This offers considerable improvement over the previous results and all the variables are found to be highly significant with correct sign across the countries concerned with the exception of a few cases. The price and income elasticities in both the demand and supply side equations carry their expected signs and significant magnitudes for the trading partners. The findings suggest that exports of Pakistan are much sensitive to changes in the world demand and world prices. This establishes the importance of demand side factors like world GDP, Real exchange rate, and world prices to determine the exports of Pakistan. On the supply side, we find relatively small price and income elasiticities. The results reveal that demand for exports is relatively higher for countries in NAFTA, European Union and Middle East regions. The study recommends particular concentration on the trade partners in these regions to improve the export performance of Pakistan. Keywords: Exports, GMM, Empirical Bayesian Method, Pakistan

Abstract 19225: Impact of Change in Resuscitation Guidelines on National Out-of-hospital Cardiac Arrest Outcomes: Fulfilled Expectations?

Circulation ◽  
2015 ◽  
Vol 132 (suppl_3) ◽  
Author(s):  
Shaker M Eid ◽  
Aiham Albaeni ◽  
Rebeca Rios ◽  
May Baydoun ◽  
Bolanle Akinyele ◽  
...  
Keyword(s):  
Time Series ◽  
Cardiac Arrest ◽  
Time Series Data ◽  
Statistical Significance ◽  
Interrupted Time Series ◽  
The United States ◽  
Series Data ◽  
National Database ◽  
Resuscitation Guidelines ◽  
Hospital Cardiac Arrest

Background: The intent of the 5-yearly Resuscitation Guidelines is to improve outcomes. Previous studies have yielded conflicting reports of a beneficial impact of the 2005 guidelines on out-of-hospital cardiac arrest (OHCA) survival. Using a national database, we examined survival before and after the introduction of both the 2005 and 2010 guidelines. Methods: We used the 2000 through 2012 National Inpatient Sample database to select patients ≥18 years admitted to hospitals in the United States with non-traumatic OHCA (ICD-9 CM codes 427.5 & 427.41). A quasi-experimental (interrupted time series) design was used to compare monthly survival trends. Outcomes for OHCA were compared pre- and post- 2005 and 2010 resuscitation guidelines release as follows: 01/2000-09/2005 vs. 10/2005-9/2010 and 10/2005-9/2010 vs. 10/2010-12/2012. Segmented regression analyses of interrupted time series data were performed to examine changes in survival to hospital discharge. Results: For the pre- and post- guidelines periods, 81600, 69139 and 36556 patients respectively survived to hospital admission following OHCA. Subsequent to the release of the 2005 guidelines, there was a statistically significant worsening in survival trends (β= -0.089, 95% CI -0.163 – -0.016, p =0.018) until the release of the 2010 guidelines when a sharp increase in survival was noted which persisted for the period of study (β= 0.054, 95% CI -0.143 – 0.251, p =0.588) but did not achieve statistical significance (Figure). Conclusion: National clinical guidelines developed to impact outcomes must include mechanisms to assess whether benefit actually occurs. The worsening in OHCA survival following the 2005 guidelines is thought provoking but the improvement following the release of the 2010 guidelines is reassuring and worthy of perpetuation.

scholarly journals Exchange Rate Dynamics and the Bilateral Trade Balance: The Case of U.S. Agriculture

2009 ◽  
Vol 38 (2) ◽  
pp. 213-228 ◽  
Author(s):  
Jungho Baek ◽  
Won W. Koo ◽  
Kranti Mulik
Keyword(s):  
United States ◽  
Exchange Rate ◽  
Bilateral Trade ◽  
Time Series Data ◽  
The United States ◽  
Agricultural Trade ◽  
Agricultural Products ◽  
Series Data ◽  
J Curve ◽  
Trading Partners

This study examines the dynamic effects of changes in exchange rates on bilateral trade of agricultural products between the United States and its 15 major trading partners. Special attention is paid to investigate whether or not the J-curve hypothesis holds for U.S. agricultural trade. For this purpose, an autoregressive distributed lag (ARDL) approach to cointegration is applied to quarterly time-series data from 1989 and 2007. Results show that the exchange rate plays a crucial role in determining the short- and long-run behavior of U.S. agricultural trade. However, we find little evidence of the J-curve phenomenon for U.S. agricultural products with the United States’ major trading partners.

Regional and Industrial Wage Dynamics in West Germany and the United States / Regionale und industrielle Lohndynamik in Westdeutschland und den USA

2002 ◽  
Vol 222 (5) ◽  
Author(s):  
Antje Mertens
Keyword(s):  
United States ◽  
Time Series Data ◽  
The United States ◽  
Labour Markets ◽  
West Germany ◽  
Series Data ◽  
Labour Demand ◽  
Wage Dynamics ◽  
Demand Shocks ◽  
Individual Level

SummaryIt is commonly known that every economy is faced with the problem of unevenly distributed labour demand changes across industries, occupations and regions. In competitive labour markets flexible wages and the mobility of labour would lead to a new equilibrium distribution of wages and employment. Regional or industrial unemployment dispersion in Germany is often blamed on a lack of wage adjustments and the lack of labour mobility when economic fortunes are not distributed evenly, but this hypothesis is hardly ever tested. This paper asks how wage reactions in Germany compare with responses in the United States using individual level data. As a first step labour demand shocks are estimated from employment time series data using deterministic detrending and the Hodrick-Prescott filter. These are then included in typical wage regressions based on micro data. The results propose that German labour markets are not as inflexible as simple evidence might suggest. Although wages are regionally only flexible in the United States, wages are found to react to industrial labour demand shocks in both countries. Especially for more experienced and therefore less mobile groups in the German labour market wages react to industrial labour demand shocks.

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