scholarly journals Impacts of Climate Factors Influencing Rice Production in Bangladesh

2021 ◽  
pp. 43-52
Author(s):  
Mahmuda Akter ◽  
Md. Mizanur Rahman Sarker
Keyword(s):  
Climate Change ◽  
Least Squares ◽  
Climate Extremes ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Rice Production ◽  
Climate Data ◽  
Average Percentage ◽  
Climate Change Pattern ◽  
Rice Yields

This study aims to study the climate change pattern, assess the situation of climate change, finding the influences of climate change on the production of rice, estimating a model between climate change and rice production in Bangladesh. Ordinary Least Squares (OLS), Generalized Least Squares (GLS), Feasible Generalized Least Squares (FGLS) were used in this study to compare the results. This study included all 64 districts of Bangladesh with a time span from 2011 to 2018. It included panel data of the production of Aus rice, Aman rice, Boro rice as well as HYV of each rice (Aus, Aman, Boro) of 64 districts of Bangladesh for agricultural data, temperature, rainfall and humidity of 64 districts for climate data. This study estimates the stochastic production function formulated by Just and Pope (1978, 1979), which allows the effect of inputs on the mean yield to differ from that on yield variance. The results showed that increased climate variability, climate extremes; in particular, exacerbate risk on Rice production in Bangladesh. Rice yields are sensitive to rainfall extremes, with both deficient and surplus rainfall increasing variability. For 1% increase in annual total rainfall, Mean Yield will decrease by 0.139%, 0.141%, 0.132% in OLS, GLS and FGLS method respectively, if other variables remaining the same. For 1% increase in annual average percentage of humidity, Mean Yield increases by 1.352%, 1.340%, 1.362% in OLS, GLS and FGLS method respectively, if other variables remaining the same. for 1% increase in HYV area, Mean Yield increases by 0.831% in OLS, GLS and FGLS method, if other variables remaining the same. Additionally, climate inputs, non-climate input, high yielding variety seeds are found to increase average yield.

scholarly journals Farmers’ Climate Change Adaptation Strategies for Reducing the Risk of Rice Production: Evidence from Rajshahi District in Bangladesh

Agronomy ◽  
2021 ◽  
Vol 11 (3) ◽  
pp. 600
Author(s):  
Shahjahan Ali ◽  
Bikash Chandra Ghosh ◽  
Ataul Gani Osmani ◽  
Elias Hossain ◽  
Csaba Fogarassy
Keyword(s):  
Climate Change ◽  
Climate Change Adaptation ◽  
Rice Production ◽  
Adaptation Strategies ◽  
Production Risk ◽  
Substantial Impact ◽  
Rice Farmers ◽  
Agronomic Practices ◽  
Rice Yields ◽  
Climate Change Adaptation Strategies

A lack of adaptive capacities for climate change prevents poor farmers from diversifying agricultural production in Bangladesh’s drought-resilient areas. Climate change adaptation strategies can reduce the production risk relating to unforeseen climatic shocks and increase farmers’ food, income, and livelihood security. This paper investigates rice farmers’ adaptive capacities to adapt climate change strategies to reduce the rice production risk. The study collected 400 farm-level micro-data of rice farmers with the direct cooperation of Rajshahi District. The survey was conducted during periods between June and July of 2020. Rice farmers’ adaptive capacities were estimated quantitatively by categorizing the farmers as high, moderate, and low level adapters to climate change adaptation strategies. In this study, a Cobb–Douglas production function was used to measure the effects of farmers’ adaptive capacities on rice production. The obtained results show that farmers are moderately adaptive in terms of adaptation strategies on climate change and the degree of adaptation capacities. Agronomic practices such as the quantity of fertilizer used, the amount of labor, the farm’s size, and extension contacts have a substantial impact on rice production. This study recommends that a farmer more significantly adjusts to adaptation strategies on climate change to reduce rice production. These strategies will help farmers to reduce the risk and produce higher quality rice. Consequently, rice farmers should facilitate better extension services and change the present agronomic practice to attain a higher adaptation status. It can be very clearly seen that low adaptability results in lower rice yields.

REDUNDANCY OF MOMENT CONDITIONS AND THE EFFICIENCY OF OLS IN SUR MODELS

2008 ◽  
Vol 24 (5) ◽  
pp. 1456-1460 ◽  
Author(s):  
Hailong Qian
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Generalized Method Of Moments ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
American Statistical Association ◽  
Orthogonality Condition ◽  
Moment Conditions ◽  
Necessary And Sufficient

In this note, based on the generalized method of moments (GMM) interpretation of the usual ordinary least squares (OLS) and feasible generalized least squares (FGLS) estimators of seemingly unrelated regressions (SUR) models, we show that the OLS estimator is asymptotically as efficient as the FGLS estimator if and only if the cross-equation orthogonality condition is redundant given the within-equation orthogonality condition. Using the condition for redundancy of moment conditions of Breusch, Qian, Schmidt, and Wyhowski (1999, Journal of Econometrics 99, 89–111), we then derive the necessary and sufficient condition for the equal asymptotic efficiency of the OLS and FGLS estimators of SUR models. We also provide several useful sufficient conditions for the equal asymptotic efficiency of OLS and FGLS estimators that can be interpreted as various mixings of the two famous sufficient conditions of Zellner (1962, Journal of the American Statistical Association 57, 348–368).

scholarly journals The effect of creative corporate culture and intangibility on the performance of foreign firms traded on the NYSE

2018 ◽  
Vol 15 (4) ◽  
pp. 356-372 ◽  
Author(s):  
Marcia Martins Mendes De Luca ◽  
Paulo Henrique Nobre Parente ◽  
Emanoel Mamede Sousa Silva ◽  
Ravena Rodrigues Sousa
Keyword(s):  
New York ◽  
Least Squares ◽  
Corporate Culture ◽  
Corporate Performance ◽  
Stock Exchange ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Foreign Firms ◽  
Content Type ◽  
Negative Effect

Purpose Following the tenets of resource-based view, the present study aims to investigate the effect of creative corporate culture according to the competing values framework model at the level of corporate intangibility and its respective repercussions on performance. Design/methodology/approach The sample included 117 non-USA foreign firms traded on the New York Stock Exchange (NYSE), which issued annual financial reports between 2009 and 2014 using the 20-F form. To meet the study objectives, in addition to the descriptive and comparative analyses, the authors performed regression analyses with panel data, estimating generalized least-squares, two-stage least-squares and ordinary least-squares. Findings Creative culture had a negative effect on the level of intangibility and corporate performance, while the level of intangibility did not appear to influence corporate performance. When combined, creative culture and intangibility had a potentially negative effect on corporate results. In conclusion, creative corporate culture had a negative effect on performance, even in firms with higher levels of intangibility, characterized by elements like experimentation and innovation. Originality/value Although the study hypotheses were eventually rejected, the analyses are relevant to both the academic setting and the market because of the organizational and institutional aspects evaluated, especially in relation to intangibility and creative culture and in view of the unique cross-cultural approach adopted. Within the corporate setting, the study provides a spectrum of stakeholders with tools to identify the profile of foreign firms traded on the NYSE.

Nuisance vs. Substance: Specifying and Estimating Time-Series-Cross-Section Models

1996 ◽  
Vol 6 ◽  
pp. 1-36 ◽  
Author(s):  
Nathaniel Beck ◽  
Jonathan N. Katz
Keyword(s):  
Time Series ◽  
Least Squares ◽  
Cross Section ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Correlated Errors ◽  
Section Data ◽  
Variable Approach ◽  
Parameter Heterogeneity ◽  
Lagged Dependent Variable

In a previous article we showed that ordinary least squares with panel corrected standard errors is superior to the Parks generalized least squares approach to the estimation of time-series-cross-section models. In this article we compare our proposed method with another leading technique, Kmenta's “cross-sectionally heteroskedastic and timewise autocorrelated” model. This estimator uses generalized least squares to correct for both panel heteroskedasticity and temporally correlated errors. We argue that it is best to model dynamics via a lagged dependent variable rather than via serially correlated errors. The lagged dependent variable approach makes it easier for researchers to examine dynamics and allows for natural generalizations in a manner that the serially correlated errors approach does not. We also show that the generalized least squares correction for panel heteroskedasticity is, in general, no improvement over ordinary least squares and is, in the presence of parameter heterogeneity, inferior to it. In the conclusion we present a unified method for analyzing time-series-cross-section data.

ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

2002 ◽  
Vol 18 (5) ◽  
pp. 1121-1138 ◽  
Author(s):  
DONG WAN SHIN ◽  
MAN SUK OH
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Characteristic Root ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Least Squares Estimator ◽  
Characteristic Roots ◽  
Generalized Least Squares Estimator ◽  
Ordinary Least Squares Estimator

For regression models with general unstable regressors having characteristic roots on the unit circle and general stationary errors independent of the regressors, sufficient conditions are investigated under which the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the generalized least squares estimator (GLSE) under the same normalization. A key condition for the asymptotic efficiency of the OLSE is that one multiplicity of a characteristic root of the regressor process is strictly greater than the multiplicities of the other roots. Under this condition, the covariance matrix Γ of the errors and the regressor matrix X are shown to satisfy a relationship (ΓX = XC + V for some matrix C) for V asymptotically dominated by X, which is analogous to the condition (ΓX = XC for some matrix C) for numerical equivalence of the OLSE and the GLSE.

Harmonizing biomass tables by generalized least squares

1985 ◽  
Vol 15 (2) ◽  
pp. 331-340 ◽  
Author(s):  
T. Cunia ◽  
R. D. Briggs
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Regression Function ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Sample Tree ◽  
Tree Data ◽  
Regression Techniques ◽  
Ordinary Least Squares Method

To construct biomass tables for various tree components that are consistent with each other, one may use linear regression techniques with dummy variables. When the biomass of these components is measured on the same sample trees, one should also use the generalized rather than ordinary least squares method. A procedure is shown which allows the estimation of the covariance matrix of the sample biomass values and circumvents the problem of storing and inverting large covariance matrices. Applied to 20 sets of sample tree data, the generalized least squares regressions generated estimates which, on the average were slightly higher (about 1%) than the sample data. The confidence and prediction bands about the regression function were wider, sometimes considerably wider than those estimated by the ordinary weighted least squares.

Twenty First Century Climate Extremes Projection and Climate Vulnerability Risk Assessment in Homogeneous Climatic Zones using high Resolution Climate Data

2020 ◽  
Author(s):  
Firdos Khan ◽  
Jürgen Pilz ◽  
Shaukat Ali ◽  
Sher Muhammad
Keyword(s):  
Climate Change ◽  
Bayesian Model Averaging ◽  
Development Program ◽  
Climate Extremes ◽  
Climate Extreme ◽  
Climate Data ◽  
Climatic Zones ◽  
Change Assessment ◽  
Climate Change Assessment ◽  
Increasing Trends

<p> Climate change assessment plays a pivotal role in impact assessment studies for better planning and management in different areas. A three-steps-integrated approach is used for climate change assessment. In the first step, homogeneous climatic zones were developed by combining two statistical approaches, cluster analysis and L-moment on the basis of Reconnaissance Drought Index (RDI).  A set of GCMs was selected for each climate zone by incorporating Bayesian Model Averaging (BMA), using the outputs of fourteen GCMs for maximum, minimum temperature and precipitation. The seven best GCMs were downscaled to higher resolution using statistical methods and considered for climate extremes assessment for each zone. The performances of GCMs are different for different climate variables, however, in some cases there is coincidence. Climate extremes were analyzed for the baseline and future periods F1 (2011-2040), F2 (2041-2070) and F3 (2071-2100) for the Representative Concentration Pathways (RCPs) 4.5 and 8.5. For precipitation under the RCP4.5, most of climate extremes have decreasing/increasing trends. Further, zone-01, zone-02, and zone-03 show increasing trends while zone-04 and zone-05 have mixed (decreasing/increasing) trends in climate extremes for all periods. For temperature, sixteen climate extreme indices were considered, some important indices are: GSL, SU25, TMAXmean, TMINmean, TN10p, TN90P, TX10p, TX90P, TNN, TNX, TXN, TXX. GSL has mixed trend (increasing/decreasing) depending on cold or hot climate zones. Similarly, TN10P and TN90P also show decreasing and increasing trends, respectively, while TX10P and TX90P have decreasing and increasing trends, respectively, in RCP4.5. TNN, TNX have mixed trends and TXN, TXX have mostly increasing trends except of few time periods in which they have decreasing and insignificant trends. The overall precipitation does not show significant changes, however, the projected intensities and frequencies are changing in future and require special consideration to save infrastructure, prevent casualties and other losses. More importantly, this study will help to address different Sustainable Development Goals of the United Nation Development Program related to climate change, hunger, environment, food security, and energy sectors.</p>

scholarly journals Optimal data processing in the ballistic laser gravimeter under the effect of correlated interference

2021 ◽  
pp. 10-16
Author(s):  
Anatolii Omelchenko ◽  
Oleksandr Vinnichenko ◽  
Pavel Neyezhmakov ◽  
Oleksii Fedorov ◽  
Volodymyr Bolyuh
Keyword(s):  
Mathematical Model ◽  
Data Processing ◽  
Least Squares ◽  
Measurement Method ◽  
Weighted Least Squares ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Gravitational Acceleration ◽  
Time Data ◽  
Hahn Polynomials

Abstract In order to develop optimal data processing algorithms in ballistic laser gravimeters under the effect of correlated interference, the method of generalized least squares is applied. In this case, to describe the interference, a mathematical model of the autoregression process is used, for which the inverse correlation matrix has a band type and is expressed through the values of the autoregression coefficients. To convert the “path-time” data from the output of the coincidence circuit of ballistic laser gravimeters to a process uniform in time, their local quadratic interpolation is used. Algorithms for data processing in a ballistic gravimeter, developed on the basis of a method of weighted least squares using orthogonal Hahn polynomials, are considered. To implement a symmetric measurement method, the symmetric Hahn polynomials, characterized by one parameter, are used. The method of mathematical modelling is used to study the gain in the accuracy of measuring the gravitational acceleration by the synthesized algorithms in comparison with the algorithm based on the method of least squares. It is shown that auto seismic interference in ballistic laser gravimeters with a symmetric measurement method can be significantly reduced by using a mathematical model of the second-order autoregressive process in the method of generalized least squares. A comparative analysis of the characteristics of the algorithms developed using the method of generalized least squares, the method of weighted least squares and the method of ordinary least squares is carried out.

scholarly journals Effect of exchange rate on trade of Afghanistan with its trade partners

2020 ◽  
pp. 9-23
Keyword(s):  
Exchange Rate ◽  
Least Squares ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Trade Partner ◽  
Independent Variable ◽  
The Exchange Rate ◽  
Trade Partners ◽  
India And China

The exchange rate is one of the most significant variables in the determination of export or import amount, and its shifts cause decrease and increase in the amount of foreign trade, so it is a prominent economic variable for trade policymaking in developing countries. This topic seeks to investigate the effect of exchange rate on Afghanistan’s do business with its partners that includes: Iran, Pakistan, India, and China. Data collected monthly from 2015 through 2017; and also time serious data used for analyses that there are one dependent variable and one independent variable. The ordinary least-squares (OLS) and generalized least squares (GLS) methods estimate 16 models. Results show that the exchange rate of trade partner of Afghanistan has insignificant effects on Afghanistan trade or Afghanistan exchange rate show unimportant effects on Afghanistan trade partners. In some models which coefficients are significant, the R2 is so small, and it shows a low level of explaining. 4 models are useful among the 16 models. Finally, we can say that the exchange rate of Afghanistan and its trade partners don’t affect the trade amount.

scholarly journals Rice, Carbon Dioxide, Climate Change, And Feeding The Future

2021 ◽  
Author(s):  
Yu-Kai Huang ◽  
Phatchaya Piriyathanasak ◽  
Witsanu Attavanich ◽  
Chengcheng J. Fei ◽  
Doo Bong Han ◽  
...  
Keyword(s):  
Climate Change ◽  
Carbon Dioxide ◽  
Prediction Models ◽  
Agricultural Research ◽  
Co2 Mitigation ◽  
Climate Data ◽  
Yield Data ◽  
Climate Change Effects ◽  
Asian Rice ◽  
Rice Yields

Abstract This study investigates the relationship between rice yields, climate change, and carbon dioxide (CO2). We integrate gridded climate data in the growing seasons and Asian rice yield data reported by the Food and Agriculture Organization with free air carbon dioxide enrichment (FACE) experimental data. Using those data, we estimate prediction models of rice yields that evolve over time and decompose effects of climate, CO2, and technological progress. The results show that atmospheric CO2 has significantly increased rice yields, with the contribution accounting for 29% to 33% of the observed yield growth. The results also reveal that increases in temperature decrease rice yields in parts of Asia, implying that both CO2 mitigation and climate change are yield growth depressing factors. The finding suggests a potential need for more agricultural research and development investment to offset CO2 mitigation and climate change effects.

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