Empirical studies of the journey to work in urban Canada

1979 ◽  
Vol 6 (2) ◽  
pp. 308-318 ◽  
Author(s):  
B. G. Hutchinson ◽  
D. P. Smith
Keyword(s):  
Census Tract ◽  
Goodness Of Fit ◽  
Labour Force ◽  
Empirical Studies ◽  
Explanatory Power ◽  
Gravity Models ◽  
Regression Equations ◽  
Distribution Models ◽  
Trip Distribution ◽  
Journey To Work

The 1971 census journey-to-work data supplemented by road-network data for 30 Canadian census areas are analyzed. The data are used to examine the degree to which the commonly used trip-generation and trip-distribution techniques might be used to synthesize journey-to-work patterns and the extent to which the parameters may be generalized across these urban areas.The extent to which intercensus-tract variations in labour force are explained by several separate measures of census-tract residential activity are analyzed by regression analysis. Dwelling-unit composition is isolated as the most effective predictor of census-tract labour force. These multiple regression equations explain from 96–99% of the intercensus-tract variations in labour force and the partial regression coefficients are consistent between census areas.Production-constrained and production-attraction-constrained forms of the gravity model are calibrated. Although conventional goodness-of-fit statistics suggest that these gravity models have a high degree of explanatory power, a detailed examination of the trip-interchange residuals shows that model performances are less than adequate. It is concluded that significant modifications to the traditional gravity trip-distribution models are required if interzonal travel demands are to be estimated with confidence.

Explanatory and forecasting capabilities of trip distribution models

1986 ◽  
Vol 13 (6) ◽  
pp. 666-673 ◽  
Author(s):  
P. Volet ◽  
B. G. Hutchinson
Keyword(s):  
Spatial Structure ◽  
Gravity Model ◽  
Distribution Model ◽  
Distribution Models ◽  
Trip Distribution ◽  
Socioeconomic Groups ◽  
Commuting Flows ◽  
Journey To Work

Trip distribution models attempt to capture two effects and these are changes in the overall scale of travel between some base year and forecast year as well as fundamental changes in commuting structure. The paper begins with a very brief discussion of observed commuting changes in the Toronto region between 1971 and 1981 using the census journey-to-work data. The abilities of a doubly constrained gravity model to emulate interzonal commuting flows in 1971 and 1981 are examined as well as its ability to forecast 1981 flows. These explanatory and forecasting capabilities are compared with those of a Fratar-type trip distribution model. The trip interchange residuals for both model types are isolated and interpreted in terms of the changes in spatial structure that have occurred in the Toronto region over the analysis period. It is concluded that the forecasts provided by the Fratar model are much superior to those of the aggregate doubly constrained gravity model. Both model types have difficulties in emulating shifts in commuting structure that are due to fundamental changes in living and working patterns by the various socioeconomic groups.

The Relative and Incremental Valuation Effects of Embedded Value Disclosure by Life Insurers: Evidence from Cross-Listed Firms in the U.S.

2014 ◽  
Vol 29 (2) ◽  
pp. 327-339 ◽  
Author(s):  
Samir M. El-Gazzar ◽  
Rudolph A. Jacob ◽  
Scott P. McGregor
Keyword(s):  
Empirical Studies ◽  
Explanatory Power ◽  
Accounting Standards ◽  
Cash Flows ◽  
Market Prices ◽  
Joint Project ◽  
Listed Firms ◽  
Valuation Effects ◽  
Life Insurers ◽  
Embedded Value

SYNOPSIS European life insurers began disclosing embedded value information (EV) over a decade ago due to concerns with traditional local accounting standards. EV is an estimate of the present value of future net cash flows from in-force life insurance business. However, U.S.-based life insurers have yet to adopt this disclosure, although several surveys and empirical studies suggest that EV disclosure provides valuable information in assessing life insurers' performance. This paper examines the incremental valuation effects of EV disclosure in the presence of U.S. GAAP. We utilize a sample of cross-listed life insurers as surrogates to assess the valuation effects of EV disclosures for U.S. life insurers. Our empirical results show a higher association between EV and stock market prices than those of traditional accounting metrics such as earnings or book value. The results also show that EV has incremental explanatory power beyond those of traditional U.S. GAAP accounting measures. Our findings provide vital input to FASB and IASB as they currently engage in a joint project to develop uniform globally acceptable, comparable accounting standards for life insurers.

Extreme price moves: an INGARCH approach to model coexceedances in commodity markets

2020 ◽  
Author(s):  
Bernardina Algieri ◽  
Arturo Leccadito
Keyword(s):  
Goodness Of Fit ◽  
Emerging Market ◽  
Explanatory Power ◽  
Commodity Markets ◽  
Credit Spread ◽  
Market Demand ◽  
Factors Affecting ◽  
Monday Effect ◽  
Tail Events ◽  
Weather Anomalies

Abstract This study presents a set of integer-valued generalised autoregressive conditional heteroskedastic models to identify possible transmission channels of joint extreme price moves (coexceedances) across a group of agricultural commodities. These models are very useful to identify factors affecting joint tail events and they are superior in terms of goodness of fit to models without autoregressive components. Emerging market demand, crude oil, exchange rate, stock market conditions and credit spread explain extreme joint returns. Psychological factors and the Monday effect play a role in affecting extreme events, while weather anomalies (El Niño and La Niña episodes) do not have explanatory power.

scholarly journals Leverage Points for Governing Agricultural Soils: A Review of Empirical Studies of European Farmers’ Decision-Making

2018 ◽  
Vol 10 (9) ◽  
pp. 3179 ◽  
Author(s):  
Bartosz Bartkowski ◽  
Stephan Bartke
Keyword(s):  
Decision Making ◽  
Goodness Of Fit ◽  
Institutional Environment ◽  
Agricultural Soils ◽  
Empirical Studies ◽  
Symbolic Capital ◽  
Empirical Literature ◽  
Behavioural Characteristics ◽  
Peer Orientation ◽  
Economic Constraints

What drives farmers’ decision-making? To inform effective, efficient, and legitimate governance of agricultural soils, it is important to understand the behaviour of those who manage the fields. This article contributes to the assessment and development of innovative soil governance instruments by outlining a comprehensive understanding of the determinants of farmers’ behaviour and decision-making. Our analysis synthesises empirical literature from different disciplines spanning the last four decades on various farm-level decision-making problems. Based on a conceptual framework that links objective characteristics of the farm and the farmer with behavioural characteristics, social-institutional environment, economic constraints, and decision characteristics, empirical findings from 87 European studies are presented and discussed. We point out that economic constraints and incentives are very important, but that other factors also have significant effects, in particular pro-environmental attitudes, goodness of fit, and past experience. Conversely, we find mixed results for demographic factors and symbolic capital. A number of potentially highly relevant yet understudied factors for soil governance are identified, including adoption of technologies, advisory services, bureaucratic load, risk aversion and social capital, social norms, and peer orientation. Our results emphasise the importance of a broad behavioural perspective to improve the efficiency, effectiveness, and legitimacy of soil governance.

scholarly journals REMUNERATIONS AND LABOUR PRODUCTIVITY IN AGRICULTURE AGAINST A BACKGROUND OF OTHER ECONOMY SECTORS

2018 ◽  
Vol 17 (1) ◽  
pp. 49-58 ◽  
Author(s):  
Justyna Góral ◽  
Włodzimierz Rembisz
Keyword(s):  
Agricultural Sector ◽  
Optimal Allocation ◽  
Labour Force ◽  
Empirical Studies ◽  
Labour Productivity ◽  
Allocation Of Resources ◽  
Economic Activities ◽  
Agricultural Producers ◽  
The Sustainable Development ◽  
Economic Growth Model

The optimal allocation of resources in various sectors results in the sustainable development of the whole economy (the theory of optimum allocation of resources by Kantonowicz and Koopmans). According to Tinbergen’s studies, the excessive labour force in one of them gives rise to all types of social and economic problems. The objective of theoretical considerations and empirical studies of this publication is to analyse the ratio of the remuneration for labour to its productivity in various economy sectors with particular attention paid to the agricultural sector. The authors also refer to the theory by Lewis and Schultz, who had analysed the problems of agriculture in developing countries, as well as to the Solow economic growth model with the Cobb–Douglas production function. In the light of the empirical data presented in the paper, we can conclude that in section A of Statistical Classification of Economic Activities this ratio is seriously disturbed and distorted. The remuneration is overvalued in relation to the labour productivity. Such a ratio is not a positive testimony to the reasonableness of management in the sense of agricultural producers’ equilibria.

scholarly journals A critical revision of the empirical literature on Chinese outward investment: A new proposal

2011 ◽  
Vol 58 (5) ◽  
pp. 715-733 ◽  
Author(s):  
Carlos Rodríguez ◽  
Ricardo Bustillo
Keyword(s):  
Global Economy ◽  
Empirical Studies ◽  
Explanatory Power ◽  
Empirical Literature ◽  
Market Size ◽  
Foreign Investors ◽  
Manufacturing Location ◽  
Critical Revision ◽  
Key Drivers ◽  
Large Host

Research on China?s role in the globalization of economic activity focuses mainly on its involvement in trade and on its competitiveness as a manufacturing location for foreign investors. However, since the mid-1990s China?s outward foreign direct investment (OFDI) has become an important part of its integration into the global economy. This dimension is poorly understood, and few empirical studies about the drivers behind Chinese OFDI have been published thus far. After reviewing critically the empirical literature, which provides ambiguous results about the explanatory power of some of the large list of determinants put forward, we aim to provide a more accurate description of the motives behind Chinese OFDI. Using a panel data approach for the period 1995 to 2009 and for a large host country sample, we identify some key drivers. We find that host market size, natural resources and FDI openness are of paramount relevance. However, the asset seeking hypothesis is not confirmed.

scholarly journals Demand prediction model for regional railway services considering spatial effects between stations

2016 ◽  
Author(s):  
Rubén Cordera Piñera ◽  
Roberto Sañudo ◽  
Luigi Dell'Olio ◽  
Ángel Ibeas
Keyword(s):  
Environmental Sustainability ◽  
Gravity Models ◽  
Spatial Effects ◽  
The European Union ◽  
Distribution Models ◽  
Railway Stations ◽  
Ticket Sales ◽  
Demand Prediction ◽  
Passenger Demand ◽  
Railway Infrastructure

The railways are a priority transport mode for the European Union given their safety record and environmental sustainability. Therefore it is important to have quantitative models available which allow passenger demand for rail travel to be simulated for planning purposes and to evaluate different policies. The aim of this article is to specify and estimate trip distribution models between railway stations by considering the most influential demand variables. Two types of models were estimated: Poisson regression and gravity. The input data were the ticket sales on a regional line in Cantabria (Spain) which were provided by the Spanish railway infrastructure administrator (ADIF – RAM). The models have also considered the possible existence of spatial effects between train stations. The results show that the models have a good fit to the available data, especial the gravity models constrained by origins and destinations. Furthermore, the gravity models which considered the existence of spatial effects between stations had a significantly better fit than the Poisson models and the gravity models that did not consider this phenomenon. The proposed models have therefore been shown to be good support tools for decision making in the field of railway planning.DOI: http://dx.doi.org/10.4995/CIT2016.2016.4053

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