An intraregional economic analysis of production structure and factor demand in major Canadian softwood lumber producing regions

1988 ◽  
Vol 18 (8) ◽  
pp. 1036-1048 ◽  
Author(s):  
J. K. Meil ◽  
J. C. Nautiyal

Cross-sectional time-series data were employed to estimate four intraregional models of production structure and factor demand over the time period 1968–1984. Lumber, tie, and pulp chip information was incorporated into the restricted, single-output, variable cost transcendental logarithmic function. Results indicate that aggregate sectoral studies do not adequately reflect regional production behaviour in the industry. Additional tests for aggregation bias demonstrated that different mill sizes within a region also portray differing production behaviour. Factor demand decomposition analysis indicated that demand for production inputs is not static, but is governed by offsetting dynamic effects. With few exceptions, all mills across regions exemplify material- and energy-using and labour-saving biases in technical change. Larger mills consistenly registered the greatest labour-saving technical change, which countered their lack of attaining significantly large cost-reducing scale economies. Mid-sized mills consistently exhibited the largest returns to scale. The data suggest that small mills are leaving the industry in some regions and production capacity is becoming concentrated in the larger mills.

2006 ◽  
Vol 36 (10) ◽  
pp. 2633-2641 ◽  
Author(s):  
James RG McQueen ◽  
Karen Potter-Witter

A translog variable cost function of the sawmill industry in Michigan, Minnesota, and Wisconsin was estimated using pooled time-series data for the period 1963–1996 with inputs labour, materials, and capital. The estimated model imposed Hicks-neutral technical change and allowed for nonconstant returns to scale as well as nonunitary elasticities of substitution amongst the inputs. Results for the Allen–Uzawa partial elasticity of substitution and the Morishima elasticity of substitution indicate that the three inputs were inelastic substitutes. The own-price elasticities of demand and the cross-price elasticities were all inelastic. The industry exhibits increasing returns to scale and positive technical change. Total factor productivity was increasing by 0.69%/year over the study period.


2020 ◽  
Vol 12 (3) ◽  
pp. 895 ◽  
Author(s):  
Cephas Paa Kwasi Coffie ◽  
Hongjiang Zhao ◽  
Isaac Adjei Mensah

The financial landscape of sub-Sahara Africa is undergoing major changes due to the advent of FinTech, which has seen mobile payments boom in the region. This paper examines the salient role of mobile payments in traditional banks’ drive toward financial accessibility in sub-Sahara Africa by using panel econometric approaches that consider the issues of independencies among cross-sectional residuals. Using data from the World Development Index (WDI) 2011–2017 on 11 countries in the region, empirical results from cross-sectional dependence (CD) tests, panel unit root test, panel cointegration test, and the fully modified ordinary least squares (FMOLS) approach indicates that (i) the panel time series data are cross-sectionally independent, (ii) the variables have the same order of integration and are cointegrated, and (iii) growth in mobile payment transactions had a significant positive relationship with formal account ownership, the number of ATMs, and number of new bank branches in the long-run. The paper therefore confirms that the institutional structure of traditional banks that makes them competitive, irrespective of emerging disruptive technologies, has stimulated overall financial accessibility in the region leading to overall sustainable growth in the financial sector. We conclude the paper with feasible policy suggestions.


Author(s):  
Andrew Q. Philips

In cross-sectional time-series data with a dichotomous dependent variable, failing to account for duration dependence when it exists can lead to faulty inferences. A common solution is to include duration dummies, polynomials, or splines to proxy for duration dependence. Because creating these is not easy for the common practitioner, I introduce a new command, mkduration, that is a straightforward way to generate a duration variable for binary cross-sectional time-series data in Stata. mkduration can handle various forms of missing data and allows the duration variable to easily be turned into common parametric and nonparametric approximations.


2020 ◽  
Vol 08 (04) ◽  
pp. 2050020
Author(s):  
Shenning QU

As an analytical framework for studying the characteristics of changes in things and their action mechanisms, the decomposition analysis of greenhouse gas emissions has been increasingly used in environmental economics research. The author introduces several decomposition methods commonly used at present and compares them. The index decomposition analysis (IDA) of carbon emissions usually uses energy identities to express carbon emissions as the product of several factor indexes, and decomposes them according to different weight-determining methods to clarify the incremental share of each index, in which way it is possible to decompose the models that contain less factors, process time series data, and conduct cross-country comparisons. It mainly includes the Laspeyres index decomposition and the Divisia index decomposition. Among them, the LMDI I method has been widely used for its advantages such as generating no residuals and easy to use. The structural decomposition analysis (SDA) can be used to conduct a more systematic analysis, decompose models with more influencing factors, and analyze the impacts of various factors on emissions, but this method has higher requirements for data collection. The biggest difference between the SDA method and the IDA methods of carbon emissions is that the former is based on an input–output system, while the latter only needs to use sectors’ aggregate data.


Author(s):  
Arini Wahyu Utami ◽  
Jamhari Jamhari ◽  
Suhatmini Hardyastuti

Paddy and maize are two important food crops in Indonesia and mainly produced in Java Island. This research aimed to know the impact of El Nino and La Nina on paddy and maize farmer’s supply in Java. Cross sectional data from four provinces in Java was combined with time series data during 1987-2006. Paddy supply was estimated using log model, while maize supply used autoregressive model; each was estimated using two types of regression function. First, it included dummy variable of El Nino and La Nina to know their influence into paddy and maize supply. Second, Southern Oscillation Index was used to analyze the supply changing when El Nino or La Nina occur. The result showed that El Nino and La Nina did not influence paddy supply, while La Nina influenced maize supply in Java. Maize supply increased when La Nina occurred.


Author(s):  
Josep Escrig Escrig ◽  
Buddhika Hewakandamby ◽  
Georgios Dimitrakis ◽  
Barry Azzopardi

Intermittent gas and liquid two-phase flow was generated in a 6 m × 67 mm diameter pipe mounted rotatable frame (vertical up to −20°). Air and a 5 mPa s silicone oil at atmospheric pressure were studied. Gas superficial velocities between 0.17 and 2.9 m/s and liquid superficial velocities between 0.023 and 0.47 m/s were employed. These runs were repeated at 7 angles making a total of 420 runs. Cross sectional void fraction time series were measured over 60 seconds for each run using a Wire Mesh Sensor and a twin plane Electrical Capacitance Tomography. The void fraction time series data were analysed in order to extract average void fraction, structure velocities and structure frequencies. Results are presented to illustrate the effect of the angle as well as the phase superficial velocities affect the intermittent flows behaviour. Existing correlations suggested to predict average void fraction and gas structures velocity and frequency in slug flow have been compared with new experimental results for any intermittent flow including: slug, cap bubble and churn. Good agreements have been seen for the gas structure velocity and mean void fraction. On the other hand, no correlation was found to predict the gas structure frequency, especially in vertical and inclined pipes.


2018 ◽  
Vol 1 (1) ◽  
pp. 62-75
Author(s):  
Pradip Raj Poudel ◽  
Narayan Raj Joshi ◽  
Shanta Pokhrel

A study on effects of climate change on rice (Oryza sativa) production in Tharu communities of Dang district of Nepal was conducted in 2018A.D to investigate the perception and major adaptation strategies followed by Tharu farmers. The study areas were selected purposively. Cross-sectional data was collected using a household survey of 120 households by applying simple random sampling technique with lottery method for sample selection. Primary data were collected using semi-structured and pretested interview schedule, focus group discussion and key informants interview whereas monthly and annual time series data on temperature and precipitation over 21years (1996-2016) were collected from Department of Hydrology and Meteorology, Kathmandu as secondary data. Descriptive statistics and trend analysis were used to analyze the data. The ratio of male and female was found to be equal with higher literacy rate at study area than district. Most of the farmers depended on agriculture only for their livelihood where there was large variation in land distribution. Farmers had better access to FM/radio for agricultural extension information sources. The study resulted that Tharu farmers of Dang perceived all parameters of climate. Temperature and rainfall were the most changing component of climate perceived by farmers. The trend analysis of temperature data of Dang over 21 years showed that maximum, minimum and average temperature were increasing at the rate of 0.031°C, 0.021°C and 0.072°C per year respectively which supports the farmers perception whereas trend of rainfall was decreased with 7.56mm per year. The yearly maximum rainfall amount was increased by 1.15mm. The production of local indigenous rice varieties were decreasing while hybrid and improved rice varieties were increasing. The district rice production trend was increasing which support the farmer’s perception. The study revealed that there were climate change effects on paddy production and using various adaptation strategies to cope in Dang district.


2017 ◽  
Vol 12 (2) ◽  
pp. 151 ◽  
Author(s):  
Yusuf Ali Al-Hroot ◽  
Laith Akram Muflih AL-Qudah ◽  
Faris Irsheid Audeh Alkharabsha

This paper intends to investigate whether the financial crisis (2008) exerted an impact on the level of accounting conservatism in the case of Jordanian commercial banks before and during the financial crisis. The sample of this study includes 78 observations; these observations are based on the financial statements of all commercial banks in Jordan and may be referred to as cross-sectional data, whereas the period from 2005 to 2011 represents a range of years characterized by time series data. The appropriate regression model to measure the relationship between cross-sectional data and time series data is in this case the pooled data regression (PDR) using the ordinary least squares (OLS) method. The results indicate that the level of accounting conservatism had been steadily increasing over a period of three years from 2005 to 2007. The results also indicate that the level of accounting conservatism was subjected to an increase during crisis period between 2009 and 2011 compared with the level of accounting conservatism for the period 2005-2007 preceding the global financial crisis. The F-test was used in order to test the significant differences between the regression coefficients for the period before and during the global financial crisis. The results indicate a positive impact on the accounting conservatism during the global financial crisis compared with the period before the global financial crisis. The p-value is 0.040 which indicates that there are statistically significant differences between the two periods; these results are consistent with the results in Sampaio (2015).


1986 ◽  
Vol 2 (3) ◽  
pp. 331-349 ◽  
Author(s):  
John J. Beggs

This article proposes the use of spectral methods to pool cross-sectional replications (N) of time series data (T) for time series analysis. Spectral representations readily suggest a weighting scheme to pool the data. The asymptotically desirable properties of the resulting estimators seem to translate satisfactorily into samples as small as T = 25 with N = 5. Simulation results, Monte Carlo results, and an empirical example help confirm this finding. The article concludes that there are many empirical situations where spectral methods canbe used where they were previously eschewed.


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