scholarly journals CLIMATE RISK ASSESSMENT FOR WHEAT PRODUCERS IN BULGARIA

2019 ◽  
Vol 17 (Suppl.1) ◽  
pp. 465-470
Author(s):  
Tanya Georgieva
Keyword(s):  
Risk Assessment ◽  
Time Series ◽  
Linear Regression ◽  
Climate Variability ◽  
Wheat Yield ◽  
Secondary Data ◽  
Climate Risk ◽  
Average Yield ◽  
Yield Variation ◽  
The Impact

The aim of this paper is to present a methodology for assessing the level of climatic risk in agriculture and to assess the risk of climate variability faced by wheat producers in Bulgaria. The analysis is based on secondary data on the average wheat yield during the period 1998 - 2018. Using a breakpoint linear regression model we estimated the predictable component in the time series of the average crop yield. Climate risk was assessed using a detrended coefficient of variation. We conclude that about 10% of the average yield variation from its typical value can be explained by the impact of random factors, among which climate variability over the period.

Análise da relação entre O3, NO e NO2 usando técnicas de regressão linear múltipla.

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

South Africa’s increasing climate variability and its effect on food production

2021 ◽  
pp. 003072702110049
Author(s):  
Mashudu Tshikovhi ◽  
Roscoe Bertrum van Wyk
Keyword(s):  
South Africa ◽  
Climate Variability ◽  
Food Production ◽  
Fixed Effects ◽  
Crop Yields ◽  
Negative Impact ◽  
Secondary Data ◽  
Mean Annual Temperature ◽  
Fixed Effects Panel Regression ◽  
The Impact

This study examines the impact of increasing climate variability on food production in South Africa, focusing on maize and wheat yields. A two-way fixed effects panel regression model was used to assess the climate variability impacts, analysing secondary data for the period 2000 to 2019 for nine provinces in South Africa. The study found that increasing climate variability has a negative impact on maize and wheat production in South Africa. Specifically, the results indicated a negative correlation between mean annual temperature with both maize and wheat yields. A decrease in precipitation affected maize yields negatively, while the impact on wheat yields was positive, although insignificant. This analysis, therefore, depicted that crop yields generally increase with more annual precipitation and decrease with higher temperatures. The study recommends that funding initiatives to educate farmers on increasing climate variability and its effects on farming activities in South Africa should be prioritised.

scholarly journals PENGARUH INVESTASI DAN TENAGA KERJA TERHADAP PRODUK DOMESTIK REGIONAL BRUTO (PDRB) DAN PENDAPATAN ASLI DAERAH (PAD) KOTA BALIKPAPAN

2015 ◽  
Vol 5 (2) ◽  
pp. 159
Author(s):  
Johana Rosmalia ◽  
Rusdiah Iskandar ◽  
Fitriadi Fitriadi
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Pathway Analysis ◽  
Secondary Data ◽  
Strong Relationship ◽  
Domestic Product ◽  
Regression Formula

This study used secondary data in the form of time series which are analyzed using Pathway analysis with multiple linear regression formula. The purpose of this study was to determine the effect of investment and labor to gross regional domestic product (GRDP) and regional revenues in Balikpapan city.  The results of the study was shown that Y = 0.202 - 0.098 X1 + 0.244 X2 + 0.825 X3. The results showed that investment, labor and gross regional domestic product (GRDP) have jointly effect on the regional revenues in Balikpapan city. Partially; the investment has no significant effect on gross regional domestic product (GRDP), labor has significant effect on gross regional domestic product (GRDP), gross regional domestic product (GRDP) has significant effect to regional revenues in Balikpapan city, the investment has no significant effect on regional revenues in Balikpapan city, and labor has no significant effect on regional revenues in Balikpapan city. The contribution of investment, labor and gross regional domestic product (GRDP) variable was about 93.5 % and it means that those have very strong relationship; meanwhile, the rest, about 6.5 %, has been influenced by other factors.

scholarly journals Impact of Crude Prices on Retail Prices – A Time Series Analysis

2019 ◽  
Vol 8 (2S7) ◽  
pp. 606-612
Keyword(s):  
Time Series ◽  
Time Series Analysis ◽  
Crude Oil ◽  
Energy Demand ◽  
Multivariate Time Series ◽  
Secondary Data ◽  
Series Analysis ◽  
Long Run ◽  
The Uk ◽  
The Impact

The UK has emerged as one of the largest producers of petroleum in the world. A significant amount of petroleum is used for fulfilling the energy demand within the country. However, the country witnessed a different trend from 2015. This is mainly due to the increase in imports of petroleum in order to meet domestic needs. To this, there is a need to identify the impact of changes exist in petrol and crude oil prices in the UK. In this context, the researcher has undertaken primary research to derive conclusions which are case specific and can comply with the research aim. The study used secondary data for the year 2015-2018 and conducted multivariate time series analysis. A series of tests including unit root, ARIMA, and co-integration tests were used to derive the results. The study found that there was an asymmetric relationship between the movements of prices of crude oil with respect to retail fuel prices in the long run. However, the study is not without limitations which are represented at the end of the study following with its future scope

scholarly journals Pengaruh Investasi Dan Inflasi Terhadap Jumlah Penduduk Miskin di Kabupaten Jember Tahun 2000-2015

2019 ◽  
Vol 6 (1) ◽  
pp. 81
Author(s):  
Abdul Latif Hamzah ◽  
Anifatul Hanim ◽  
Herman Cahyo
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Secondary Data ◽  
Poor People ◽  
Poverty Level ◽  
Total Investment ◽  
Year 2000 ◽  
Very High

Conditions in Jember Regency from year to year economic growth is quite high, but the poverty level is very high as well. This study aims to determine the effect of investment and inflation on the number of poor people in the district of Jember in 2000- 2015. The method used in this research is multiple linear regression. The data used are secondary data formed in time series, the data used include investment, inflation in Jember district for 16 years in the year 2000-2015. Based on the results of the research, it can be seen that investment variables do not significantly affect the number of poor people in Jember, while Inflation has a significant effect on the number of poor people in Jember. Keywords: total investment, inflation, and poor people.

Pengaruh pertumbuhan ekonomi, inflasi dan pengangguran terhadap tingkat kemiskinan di Sumatera Selatan

2019 ◽  
Vol 16 (1) ◽  
pp. 1-10
Author(s):  
Novegya Ratih Primandari
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Linear Regression ◽  
Linear Regression Model ◽  
Time Series Data ◽  
Secondary Data ◽  
Poverty Rate ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square

This research aims to analyze effect of economic growth, inflation and Unemployment on the Rate of Poverty in the Province of South Sumatera. This research used secondary data in the form of time series data from 2001-2017. The method used quantitative approach by applying a linear regression model with OLS estimation Ordinary Least Square (OLS) method. The results of this study indicate that partially and simultaneously Economic Growth, Inflation and Unemployment have a significant effect on the Poverty Rate in the Province of South Sumatera.

Using a penetrometer to predict the effects of soil compaction on the growth and yield of wheat on uniform, sandy soils

1989 ◽  
Vol 40 (3) ◽  
pp. 497 ◽  
Author(s):  
CWL Henderson
Keyword(s):  
Soil Compaction ◽  
Wheat Yield ◽  
Sandy Soils ◽  
Penetration Resistance ◽  
Growth And Yield ◽  
Single Index ◽  
Yield Variation ◽  
Soil Penetration Resistance ◽  
Good Potential ◽  
The Impact

The relationships between soil penetration resistance and the growth and yield of wheat were examined for a range of tillage and compaction experiments conducted on earthy sands near Geraldton, W.A. Overall, a single index of penetration resistance explained around 50% of the growth and yield variation, across sites and seasons. Equations using this index showed good potential for predicting the impact of various tillage and traffic practices on wheat yield.

scholarly journals Assessing climate risks in rainfed farming using farmer experience, crop calendars and climate analysis

2015 ◽  
Vol 153 (8) ◽  
pp. 1380-1393 ◽  
Author(s):  
U. B. NIDUMOLU ◽  
P. T. HAYMAN ◽  
Z. HOCHMAN ◽  
H. HORAN ◽  
D. R. REDDY ◽  
...  
Keyword(s):  
Risk Assessment ◽  
Boundary Object ◽  
Climate Risk ◽  
Seasonal Forecasts ◽  
Bottom Up ◽  
Climate Risks ◽  
Rainfed Farming ◽  
Climate Records ◽  
Climate Analysis ◽  
The Impact

SUMMARYClimate risk assessment in cropping is generally undertaken in a top-down approach using climate records while critical farmer experience is often not accounted for. In the present study, set in south India, farmer experience of climate risk is integrated in a bottom-up participatory approach with climate data analysis. Crop calendars are used as a boundary object to identify and rank climate and weather risks faced by smallhold farmers. A semi-structured survey was conducted with experienced farmers whose income is predominantly from farming. Interviews were based on a crop calendar to indicate the timing of key weather and climate risks. The simple definition of risk as consequence × likelihood was used to establish the impact on yield as consequence and chance of occurrence in a 10-year period as likelihood. Farmers’ risk experience matches well with climate records and risk analysis. Farmers’ rankings of ‘good’ and ‘poor’ seasons also matched up well with their independently reported yield data. On average, a ‘good’ season yield was 1·5–1·65 times higher than a ‘poor’ season. The main risks for paddy rice were excess rains at harvesting and flowering and deficit rains at transplanting. For cotton, farmers identified excess rain at harvest, delayed rains at sowing and excess rain at flowering stages as events that impacted crop yield and quality. The risk assessment elicited from farmers complements climate analysis and provides some indication of thresholds for studies on climate change and seasonal forecasts. The methods and analysis presented in the present study provide an experiential bottom-up perspective and a methodology on farming in a risky rainfed climate. The methods developed in the present study provide a model for end-user engagement by meteorological agencies that strive to better target their climate information delivery.

scholarly journals ANÁLISE DA RELAÇÃO ENTRE O3, NO E NO2 USANDO TÉCNICAS DE REGRESSÃO LINEAR MÚLTIPLA

GEOgraphia ◽  
2018 ◽  
Vol 20 (43) ◽  
pp. 124 ◽  
Author(s):  
Amaury De Souza ◽  
Priscilla V Ikefuti ◽  
Ana Paula Garcia ◽  
Debora A.S Santos ◽  
Soetania Oliveira
Keyword(s):  
Time Series ◽  
Linear Regression ◽  
Nitrogen Dioxide ◽  
Multiple Linear Regression ◽  
Quality Parameters ◽  
Environmental Pollutant ◽  
Environmental Research ◽  
Linear Regression Models ◽  
Mato Grosso ◽  
The Impact

Análise e previsão de parâmetros de qualidade do ar são tópicos importantes da pesquisa atmosférica e ambiental atual, devido ao impacto causado pela poluição do ar na saúde humana. Este estudo examina a transformação do dióxido de nitrogênio (NO2) em ozônio (O3) no ambiente urbano, usando o diagrama de séries temporais. Foram utilizados dados de concentração de poluentes ambientais e variáveis meteorológicas para prever a concentração de O3 na atmosfera. Foi testado o emprego de modelos de regressão linear múltipla como ferramenta para a predição da concentração de O3. Os resultados indicam que o valor da temperatura e a presença de NO2 influenciam na concentração de O3 em Campo Grande, capital do Estado do Mato Grosso do Sul. Palavras-chave: Ozônio. Dióxido de nitrogênio. Séries cronológicas. Regressões. ANALYSIS OF THE RELATIONSHIP BETWEEN O3, NO AND NO2 USING MULTIPLE LINEAR REGRESSION TECHNIQUES.Abstract: Analysis and prediction of air quality parameters are important topics of current atmospheric and environmental research due to the impact caused by air pollution on human health. This study examines the transformation of nitrogen dioxide (NO2) into ozone (O3) in the urban environment, using the time series diagram. Environmental pollutant concentration and meteorological variables were used to predict the O3 concentration in the atmosphere. The use of multiple linear regression models was tested as a tool to predict O3 concentration. The results indicate that the temperature value and the presence of NO2 influence the O3 concentration in Campo Grande, capital of the State of Mato Grosso do Sul.Keywords: Ozone. Nitrogen dioxide. Time series. Regressions. ANÁLISIS DE LA RELACIÓN ENTRE O3, NO Y NO2 UTILIZANDO MÚLTIPLES TÉCNICAS DE REGRESIÓN LINEAL.Resumen: Análisis y previsión de los parámetros de calidad del aire son temas importantes de la actual investigación de la atmósfera y el medio ambiente, debido al impacto de la contaminación atmosférica sobre la salud humana. Este estudio examina la transformación del dióxido de nitrógeno (NO2) en ozono (O3) en el entorno urbano, utilizando el diagrama de series de tiempo. Las concentraciones de los contaminantes ambientales de datos y variables climáticas fueron utilizadas para predecir la concentración de O3 en la atmósfera. El uso de múltiples modelos de regresión lineal como herramienta para predecir la concentración de O3 se puso a prueba. Los resultados indican que el valor de la temperatura y la presencia de NO2 influyen en la concentración de O3 en Campo Grande, capital del Estado de Mato Grosso do Sul.Palabras clave: Ozono. Dióxido de nitrógeno. Series de tiempo. Regresiones.

scholarly journals The Effect of Human Capital, Labors, and Capital on Economic Growth in Barlingmascakeb

2018 ◽  
Vol 13 (2) ◽  
Author(s):  
Rizqia Mutiara Sani ◽  
Herman Sambodo ◽  
Bambang Bambang
Keyword(s):  
Economic Growth ◽  
Time Series ◽  
Human Capital ◽  
Linear Regression ◽  
Life Expectancy ◽  
Secondary Data ◽  
Positive Influence ◽  
Level Of Education ◽  
Central Java ◽  
Central Java Province

The economic growth of Banjarnegara, Purbalingga, Banyumas, Cilacap and Kebumen regencies or known as Barlingmascakeb region is on average lower than the economic growth of Central Java Province. This study aims to analyze the influence of human capital that proxy from level of education and life expectacy, labor, and capital on economic growth in the Barlingmascakeb region. The data used is secondary data, time series starting from 2008-2015. This study uses multiple linear regression. Based on the results of the study it is known that the variable human capital, which is seen from the level of education and life expectancy, labor, capital has a positive influence on economic growth in the Barlingmascakeb region.Keywords: Level of Education, Life Expectancy, Labor, Capital, Economic Growth.

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