Consistent estimation of long-run nonindustrial private forest owner timber supply using micro data

2007 ◽  
Vol 37 (8) ◽  
pp. 1485-1494 ◽  
Author(s):  
Ibrahim M. Favada ◽  
Jari Kuuluvainen ◽  
Jussi Uusivuori
Keyword(s):  
Forest Owner ◽  
Private Forest ◽  
Timber Supply ◽  
Cross Sectional ◽  
Data Set ◽  
Goods And Services ◽  
Long Run ◽  
Rotation Age ◽  
Nonindustrial Private Forest ◽  
Rotation Model

In this paper, the effects of stumpage prices and forest and landowner characteristics on nonindustrial private forest owners’ long-run timber supply are examined using cross-sectional variation in a data set of 1860 landowners in Finland during 1994–1998. We estimate an inverse hyperbolic sine Tobit model allowing for heteroscedasticity and non-normality of errors. The hypotheses of the rotation model can be examined by decomposing the effects of the exogenous variables into the effects on the conditional mean of nonzero harvests and the effects on the probability of nonzero harvest. The results of the study are consistent with the Faustmann rotation model when the forest owner simultaneously decides both the optimal rotation age of an even-aged stand and the optimal life-cycle consumption of goods and services with in situ valuation of standing timber.

Impacts of technical assistance on private nonindustrial reforestation

1990 ◽  
Vol 20 (11) ◽  
pp. 1804-1810 ◽  
Author(s):  
Michael D. Skinner ◽  
W. David Klemperer ◽  
Robert J. Moulton
Keyword(s):  
Cost Sharing ◽  
Technical Assistance ◽  
Tree Planting ◽  
Private Forest ◽  
Cross Sectional ◽  
Southern States ◽  
Relevant Variables ◽  
Nipf Owners ◽  
Nonindustrial Private Forest ◽  
The Relationship

This study explores the relationship between the number of foresters providing assistance to nonindustrial private forest (NIPF) owners in the southern United States and the NIPF acres planted with pine. For the year 1985, for 29 substate zones in 12 southern states, data were gathered on numbers of NIPF assistance foresters by four types, NIPF acres planted with pine, and several other variables thought to influence levels of pine planting. Using this data, a cross-sectional regression analysis was unable to demonstrate a significant south-wide effect of technical assistance on NIPF tree planting when all significant variables were included in the equations. Within the range of data gathered, equations showed that additional cost sharing and the accompanying forestry assistance should increase reforestation, but added forestry assistance alone is less likely to influence reforestation. Some previous studies support our results, others do not. In the future, if better data on the relevant variables are gathered, more definitive conclusions might be reached about the effects of technical assistance on NIPF reforestation.

Evaluation of forestry programs: the with–without analysis

1984 ◽  
Vol 14 (4) ◽  
pp. 506-511 ◽  
Author(s):  
Patrice A. Harou
Keyword(s):  
Forest Management ◽  
Social Benefit ◽  
Private Forest ◽  
Forest Land ◽  
Timber Supply ◽  
Unmanaged Forest ◽  
Nonindustrial Private Forest ◽  
Forestry Programs

The with–without analysis used in the evaluation of forestry programs, which are aimed at increasing timber supply from nonindustrial private forest land, offers much leeway for interpretation. Three factors have an important effect on the quantification of a program's net marginal social benefit: the information on yield for managed and unmanaged forest, the behavior of the program participants, and the existence of already existing forestry programs and laws affecting forest management.

scholarly journals Determinants of Nonindustrial Private Forest Owners’ Willingness to Harvest Timber in Norway

Forests ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 60 ◽  
Author(s):  
Altamash Bashir ◽  
Hanne K. Sjølie ◽  
Birger Solberg
Keyword(s):  
Probit Model ◽  
Economic Security ◽  
Tobit Model ◽  
Forest Growth ◽  
Forest Owner ◽  
Private Forest ◽  
Private Forest Owners ◽  
Timber Supply ◽  
Forest Owners ◽  
Study Results

In Norway, 84% of the productive forest is privately owned, and these forests dominate the supply of timber to industries. However, during last 80 years, annual forest growth has seen a substantial upsurge while annual timber harvest has been rather stable, generating an increasing potential for timber supply. In this study, we provide new insights to better understand Norwegian non-industrial private forest owners’ timber harvesting decisions. This was achieved by comparing the outcomes of two different statistical approaches (i.e., a combination of probit-linear models with a tobit model). These approaches are commonly applied in timber supply studies, but to the best of our knowledge have never been compared on the same dataset. The survey utilized for this study constitutes a population of Active and Inactive forest owners, based on whether the owner had harvested timber for sale during the last fifteen years. Two gross samples of 1500 and 1650 were drawn, with response rates of 56% and 49% for the Active and Inactive owner samples, respectively. The study results reveal that the average holding size varied from 25.2 ha for Inactive to 49.5 ha for both samples and 73.8 ha for Active owners. The probit model analysis indicated that knowledge of forest fund and financial objectives had the most significant impact on the willingness to harvest, with marginal effects of 11% and 12%, respectively. In the linear regression, being a male owner increased the historical timber supply by 1.48 m3 ha−1 year−1 compared to female ownership. In the second regression pathway (tobit model), the two variables male forest owner and owning forests for financial objectives triggered the supply of timber by 1.85 m3 ha−1 year−1 and 1.25 m3 ha−1 year−1, respectively. Timber prices were significant in the linear model (elasticity 1.18) and tobit model (elasticity 0.66), whereas they were non-significant in the probit model. Our study concludes that Active owners had a better understanding of acknowledging forests for economic security. Policy-makers and extension services should recognize that the Inactive forest owner group may require different actions than Active owners.

Suicide Ideation and Attempt in a Community Cohort of Urban Aboriginal Youth: A Cross-Sectional Study

Crisis ◽  
2013 ◽  
Vol 34 (4) ◽  
pp. 251-261 ◽  
Author(s):  
Joanne N. Luke ◽  
Ian P. Anderson ◽  
Graham J. Gee ◽  
Reg Thorpe ◽  
Kevin G. Rowley ◽  
...  
Keyword(s):  
Health Service ◽  
Indigenous People ◽  
Suicide Ideation ◽  
Aboriginal Health ◽  
Cross Sectional ◽  
Data Set ◽  
Indigenous Youth ◽  
Aboriginal Youth ◽  
Social Distress ◽  
Suicide Behavior

Background: There has been increasing attention over the last decade on the issue of indigenous youth suicide. A number of studies have documented the high prevalence of suicide behavior and mortality in Australia and internationally. However, no studies have focused on documenting the correlates of suicide behavior for indigenous youth in Australia. Aims: To examine the prevalence of suicide ideation and attempt and the associated factors for a community 1 The term ”community” refers specifically to Koori people affiliated with the Victorian Aboriginal Health Service. cohort of Koori 2 The term ”Koori” refers to indigenous people from the south-eastern region of Australia, including Melbourne. The term ”Aboriginal” has been used when referring to indigenous people from Australia. The term ”indigenous” has been used throughout this article when referring to the first people of a nation within an international context. (Aboriginal) youth. Method: Data were obtained from the Victorian Aboriginal Health Service (VAHS) Young People’s Project (YPP), a community initiated cross-sectional data set. In 1997/1998, self-reported data were collected for 172 Koori youth aged 12–26 years living in Melbourne, Australia. The data were analyzed to assess the prevalence of current suicide ideation and lifetime suicide attempt. Principal components analysis (PCA) was used to identify closely associated social, emotional, behavioral, and cultural variables at baseline and Cox regression modeling was then used to identify associations between PCA components and suicide ideation and attempt. Results: Ideation and attempt were reported at 23.3% and 24.4%, respectively. PCA yielded five components: (1) emotional distress, (2) social distress A, (3) social distress B, (4) cultural connection, (5) behavioral. All were positively and independently associated with suicide ideation and attempt, while cultural connection showed a negative association. Conclusions: Suicide ideation and attempt were common in this cross-section of indigenous youth with an unfavorable profile for the emotional, social, cultural, and behavioral factors.

Dynamic Relationship between Crude Oil and Stock Prices in India: Before And After the Subprime Financial Crisis 2008

GIS Business ◽  
2019 ◽  
Vol 14 (6) ◽  
pp. 96-104
Author(s):  
P. Sakthivel ◽  
S. Rajaswaminathan ◽  
R. Renuka ◽  
N. R.Vembu
Keyword(s):  
Financial Crisis ◽  
Crude Oil ◽  
Stock Prices ◽  
Oil Prices ◽  
Energy Index ◽  
Data Set ◽  
Dynamic Relationship ◽  
Crude Oil Prices ◽  
Long Run ◽  
Before And After

This paper empirically discovered the inter-linkages between stock and crude oil prices before and after the subprime financial crisis 2008 by using Johansan co-integration and Granger causality techniques to explore both long and short- run relationships.  The whole data set of Nifty index, Nifty energy index, BSE Sensex, BSE energy index and oil prices are divided into two periods; before crisis (from February 15, 2005 to December31, 2007) and after crisis (from January 1, 2008 to December 31, 2018) are collected and analyzed. The results discovered that there is one-way causal relationship from crude oil prices to Nifty index, Nifty energy index, BSE Sensex and BSE energy index but not other way around in both periods. However, a bidirectional causality relationship between BSE Energy index and crude oil prices during post subprime financial crisis 2008. The co-integration results suggested that the absence of long run relationship between crude oil prices and market indices of BSE Sensex, BSE energy index, Nifty index and Nifty energy index before and after subprime financial crisis 2008.

Financial distress determinants among SMEs: empirical evidence from Sweden

2020 ◽  
Vol 47 (3) ◽  
pp. 547-560 ◽  
Author(s):  
Darush Yazdanfar ◽  
Peter Öhman
Keyword(s):  
Financial Crisis ◽  
Financial Distress ◽  
Large Scale ◽  
Global Financial Crisis ◽  
Binary Logistic Regression ◽  
Data Availability ◽  
Cross Sectional ◽  
Data Set ◽  
Content Type ◽  
The Global Financial Crisis

PurposeThe purpose of this study is to empirically investigate determinants of financial distress among small and medium-sized enterprises (SMEs) during the global financial crisis and post-crisis periods.Design/methodology/approachSeveral statistical methods, including multiple binary logistic regression, were used to analyse a longitudinal cross-sectional panel data set of 3,865 Swedish SMEs operating in five industries over the 2008–2015 period.FindingsThe results suggest that financial distress is influenced by macroeconomic conditions (i.e. the global financial crisis) and, in particular, by various firm-specific characteristics (i.e. performance, financial leverage and financial distress in previous year). However, firm size and industry affiliation have no significant relationship with financial distress.Research limitationsDue to data availability, this study is limited to a sample of Swedish SMEs in five industries covering eight years. Further research could examine the generalizability of these findings by investigating other firms operating in other industries and other countries.Originality/valueThis study is the first to examine determinants of financial distress among SMEs operating in Sweden using data from a large-scale longitudinal cross-sectional database.

scholarly journals Panel Econometric Analysis on Mobile Payment Transactions and Traditional Banks Effort toward Financial Accessibility in Sub-Sahara Africa

2020 ◽  
Vol 12 (3) ◽  
pp. 895 ◽  
Author(s):  
Cephas Paa Kwasi Coffie ◽  
Hongjiang Zhao ◽  
Isaac Adjei Mensah
Keyword(s):  
Time Series Data ◽  
Unit Root Test ◽  
Panel Cointegration ◽  
Ordinary Least Squares ◽  
Sustainable Growth ◽  
Series Data ◽  
Mobile Payment ◽  
Cross Sectional ◽  
Mobile Payments ◽  
Long Run

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.

scholarly journals Machine Learning in Futures Markets

2021 ◽  
Vol 14 (3) ◽  
pp. 119
Author(s):  
Fabian Waldow ◽  
Matthias Schnaubelt ◽  
Christopher Krauss ◽  
Thomas Günter Fischer
Keyword(s):  
Machine Learning ◽  
Futures Markets ◽  
Learning Models ◽  
Cross Sectional ◽  
Data Set ◽  
Statistical Arbitrage ◽  
Out Of Sample ◽  
Sample Testing ◽  
Arbitrage Strategy ◽  
Machine Learning Models

In this paper, we demonstrate how a well-established machine learning-based statistical arbitrage strategy can be successfully transferred from equity to futures markets. First, we preprocess futures time series comprised of front months to render them suitable for our returns-based trading framework and compile a data set comprised of 60 futures covering nearly 10 trading years. Next, we train several machine learning models to predict whether the h-day-ahead return of each future out- or underperforms the corresponding cross-sectional median return. Finally, we enter long/short positions for the top/flop-k futures for a duration of h days and assess the financial performance of the resulting portfolio in an out-of-sample testing period. Thereby, we find the machine learning models to yield statistically significant out-of-sample break-even transaction costs of 6.3 bp—a clear challenge to the semi-strong form of market efficiency. Finally, we discuss sources of profitability and the robustness of our findings.

scholarly journals Symptoms of acute transfusion reactions at a general referral hospital in Kinshasa, Democratic Republic of Congo: a cross-sectional study

BMJ Open ◽  
2021 ◽  
Vol 11 (7) ◽  
pp. e045081
Author(s):  
Patou Masika Musumari ◽  
Samclide Mutindu Mbikayi ◽  
Kriengkrai Srithanaviboonchai ◽  
Teeranee Techasrivichien ◽  
Arunrat Tangmunkongvorakul ◽  
...  
Keyword(s):  
Blood Transfusion ◽  
Respiratory Distress ◽  
Democratic Republic ◽  
Democratic Republic Of Congo ◽  
Referral Hospital ◽  
Sub Saharan Africa ◽  
Cross Sectional ◽  
Data Set ◽  
Republic Of Congo ◽  
Transfusion Reactions

ObjectivesBlood transfusion is a life-saving procedure and is also associated with a range of risks including the occurrence of symptoms of acute transfusion reactions (ATRs). Very few studies in sub-Saharan Africa have reported on ATRs. The present study addresses this gap in the literature by documenting the prevalence of and factors associated with ATRs in the Democratic Republic of Congo (DRC).DesignThis is a cross-sectional descriptive and analytical study using blood bank data from a general referral hospital.SettingCentre Hospitalier Mère-Enfant (CHME) Monkole, a general referral hospital in Kinshasa, DRC.ParticipantsGeneral population who have received blood transfusion in CHME Monkole between 2014 and 2019.ResultsThe data set included a total of 7166 patients; 3153 (44%) men and 4013 (56%) women. The overall prevalence of symptoms of ATRs was 2.6%; the lowest prevalence was in 2017 (2.34%) and highest in 2018 (2.95%) and 2019 (2.94%). The documented symptoms included 74 (39.6%) cases of dyspnoea/respiratory distress, 60 (32.1%) cases of fever, 36 (19.2%) cases of pruritus/urticaria and 17 (9.1%) cases of vomiting. None of the studied factors was associated with symptoms of ATRs.ConclusionSymptoms of ATRs were not uncommon in the studied population. Dyspnoea and respiratory distress, fever and pruritus/urticaria were the most common symptoms of ATRs. This study highlights the need for a clinical and biological surveillance to detect, prevent and manage ATRs in the context of the DRC.

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