Effect of Petroleum Pricing on Agricultural Production in Nigeria

2015 ◽  
Vol 6 (3) ◽  
pp. 17-28
Author(s):  
Isaac B. Oluwatayo ◽  
Henrietta U. Ukpe
Keyword(s):  
Agricultural Production ◽  
Time Series Data ◽  
Least Square ◽  
Sub Saharan Africa ◽  
Series Data ◽  
National Bureau ◽  
Lower Growth ◽  
Agricultural Output ◽  
The World ◽  
Increasing Trend

Nigeria is a dominant economic force in sub-Saharan Africa with a strong economy as well as booming oil and agricultural sectors. However, over-dependence on the production and export of oil as well as food imports has rendered the economy vulnerable to global price fluctuations. The increasing spate of fluctuations in the world price of oil affects not only the economic sector but also agricultural production. Despite the huge earnings from oil, Nigeria remains one of the most food insecure countries in the world. This study therefore estimates the effect of petrol or premium motor spirit (PMS) pricing on agricultural production using available time series data for 41 years (1970-2010) obtained from the Central Bank of Nigeria's Annual Statistical Reports and National Bureau of Statistic's Bulletins. The study reveals that the trend in production level of agricultural products persistently increased between 1984 and 2000, followed by a much lower growth rate between 2001 and 2002 sub-period and the increasing trend picked up again in 2003. There was an increasing trend pattern of petrol (PMS) prices except for 2009 when the price dropped from N70 to N65. Consumption of PMS was not relatively constant either. The Ordinary Least Square (OLS) results show that the quantity of agricultural output increased with the price of PMS. However, consumption of PMS had an inverse relationship with agricultural output.

Seasonal and interannual variation of decapod larval abundance from two coastal locations in Scotland, UK

2011 ◽  
Vol 91 (7) ◽  
pp. 1443-1451 ◽  
Author(s):  
Maria Pan ◽  
Graham J. Pierce ◽  
Carey O. Cunningham ◽  
Steve J. Hay
Keyword(s):  
East Coast ◽  
Time Series Data ◽  
Least Square ◽  
Series Data ◽  
Larval Abundance ◽  
Square Functions ◽  
North West ◽  
North East ◽  
Increasing Trend ◽  
Decapod Larvae

The patterns of decapod larvae occurrence and abundance were studied from weekly time-series data of 8 years from Stonehaven (north-east Scotland) and 4 years and 8 months from Loch Ewe (north-west Scotland). The annual cycle observed was similar in the two locations and characterized by abundance peaks, the first in spring and another in the summer, extending into autumn. During the coldest months (December to February) decapod larvae were virtually absent in the plankton. Differences in abundance and occurrence of decapod larvae between locations and the influence of temperature, salinity and chlorophyll-a in the patterns observed, were analysed by generalized least-square functions. The results showed significant differences in the abundance of decapod larvae between locations, with higher larval abundances and an earlier appearance in the plankton in Loch Ewe (west coast). In Stonehaven (east coast), from 2003 onwards, a general increasing trend in the abundance of decapod larvae was observed, related to the increasing temperatures recorded at that site. The data demonstrate the high variability of decapod larval abundance on an annual basis and the high importance of temperature and chlorophyll-a to the occurrence and abundance of decapod larvae.

scholarly journals Impacts of climate change on agricultural production in Nepal: Case of Kavre and Jumla districts

2014 ◽  
Vol 2 ◽  
pp. 43-50
Author(s):  
K.S. Pandey ◽  
H. Shrestha ◽  
L.P. Devkota
Keyword(s):  
Climate Change ◽  
Agricultural Production ◽  
Time Series Data ◽  
Negative Impact ◽  
Wheat Yield ◽  
Series Data ◽  
National Bureau ◽  
Specific Objective ◽  
Analytical Tools ◽  
The Impact

The study the analyzed relationship of climate change with agricultural production in Kavre and Jumla districts. The specific objective of the study was to find out the dimension and linkage between agricultural production and climatic parameters in Kavre and Jumla. Time series data were analysed for the study. The data was sourced from the Department of Hydrology Meteorology, Department of Agriculture, and National Bureau of Statistics. Descriptive statistics, linear analysis test and back ward difference filter were the analytical tools used to determine the impact of climate change on productivity. During harvest period, the correlation of rice yield with temperature and rainfall was negative at Kavre but positive at Jumla. Similarly, the correlation of wheat yield with temperature and rainfall was positive at Kavre but negative at Jumla. The result showed that extreme fluctuation in weather caused negative impact on production in Jumla in compared to Kavre districts.

scholarly journals Does Exchange Rate Devaluation Affect Agricultural Output? Evidence from Nigeria

2018 ◽  
Vol 9 (2) ◽  
pp. 115-123 ◽  
Author(s):  
Olubukoye Opeyemi Oye ◽  
Adedoyin Isola Lawal ◽  
Ann Eneogu ◽  
Joseph IseOlorunkanmi
Keyword(s):  
Exchange Rate ◽  
Time Series Data ◽  
Real Effective Exchange Rate ◽  
Series Data ◽  
National Bureau ◽  
Causality Test ◽  
Agricultural Output ◽  
The Real ◽  
Effective Exchange ◽  
Effective Exchange Rate

The purpose of this research was to examine the effect of exchange rate devaluation on agricultural output in Nigeria. This investigation used the available time series data of 30 years (1986-2016) from the Central Bank of Nigeria (CBN) Statistical Bulletin and the National Bureau of Statistics. Moreover, the real effective exchange rate was used as the proxy for currency devaluation and Consumer Price Index (CPI) was used as a proxy for inflation. Other variables were Agricultural Gross Domestic Product (AGDP), Price of Export (PEXP), and Real Agricultural Exports (RAEXP). The research through the Augmented Dickey Fuller (ADF) and Philip Perron’s unit root tests find that the variables used in the model are integrated in the same order. Using the Johansen’s cointegration test results show that the variables are cointegrated. The results of the Vector Error Correction Model (VECM) indicates that a percent increase in the Real Effective Exchange Rate (REER), a proxy for devaluation. It will lead to a decrease in gross agricultural output. This implies that total agricultural output responds negatively to exchange rate devaluation. The result of the causality test by Toda and Yamamoto reveals that a unidirectional causality exists between real effective exchange rate and price of exports. This shows that a significant relationship exists between exchange rate devaluation and gross exports earnings. It reveals that the past values of the price of exports can be used to predict the current values of agricultural output.

Convergence and determinants of change in nutrient supply

2015 ◽  
Vol 117 (12) ◽  
pp. 2880-2898 ◽  
Author(s):  
Kolawole Ogundari ◽  
Shoichi Ito
Keyword(s):  
Time Series Data ◽  
Trade Openness ◽  
Nutrient Supply ◽  
Least Square ◽  
Sub Saharan Africa ◽  
Series Data ◽  
Cross Sectional ◽  
Content Type ◽  
Convergence Process ◽  
Per Capita

Purpose – The purpose of this paper is to use cross-country data to investigate whether convergence process exists in per capital nutrient supply and also identify the determinants of change in per capita nutrient supply in sub-Saharan Africa (SSA). Design/methodology/approach – Annual time series data for 43 countries covering 1975-2009 that yields balanced panel were employed for the analysis. The convergence hypothesis is examined based on the neoclassical growth model using feasible generalized least square approach that is robust to autocorrelation and cross-sectional dependence. Findings – The empirical results lend support to existence of convergence process in nutrient supply in SSA. Evidence of convergence in nutrient supply may have contributed to observed reduction in incidence of food-poverty in the region, which aligns with the argument in literature that recent Africa food security gains are due to food imports. The results of the determinants of change in nutrient supply showed that, global food trade represented by trade openness consistently increased growth in nutrient supply across countries in SSA significantly. Meanwhile, the speed of convergence of per capita nutrient supply, which measures how quickly growth in nutrient supply increases over time is very low, as this calls for urgent policy attention in the region. Originality/value – The very first study to investigate convergence in food consumption and nutritional supply in SSA.

scholarly journals Influence of road transport infrastructure on agricultural sector development in Nigeria

2018 ◽  
Vol 9 (1) ◽  
pp. 39-50 ◽  
Author(s):  
Olusogo Ogunleye ◽  
Akinyemi Ajibola ◽  
Oluwafemi Enilolobo ◽  
Olufolakemi Shogunle
Keyword(s):  
Agricultural Development ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Road Construction ◽  
Road Transport ◽  
Least Square ◽  
Transport Infrastructure ◽  
Series Data ◽  
National Bureau ◽  
Causality Test

AbstractThe study investigated the effects of road transport infrastructure on agricultural sector development in Nigeria from 1985 to 2014, using secondary annual time series data on agricultural development (proxy by gross domestic product in the Agric sector) road transport infrastructure (proxy by length of paved road per square kilometer of area) export and capital, all obtained from the Central Bank of Nigeria (CBN) [3], and National Bureau of Statistics (NBS) [16], statistical bulletins. The data were analyzed using Granger Causality test and Ordinary Least Square estimation techniques. The study concluded that a positive and statistically significant relationship exists between road transport infrastructures (LRT) also evidence was found of a unidirectional causality from agricultural sector development to transport infrastructure. The study, therefore, recommends that adequate and timely maintenance of existing roads should be carried out as well as enacting appropriate regulations that ensure proper implementation and completion of new road construction contracts in the country in order to boost agricultural sector development, reduce wastage of farm produce and increase the possibility of economic diversification.

scholarly journals MODEL PENAWARAN DAN PERMINTAAN MINYAK KELAPA SAWIT INDONESIA DI PASAR INTERNASIONAL

2020 ◽  
Vol 35 (3) ◽  
pp. 119-128
Author(s):  
Tia Sofiani Napitupulu ◽  
Djaimi B Akce ◽  
Almasdi Syahza ◽  
Brilliant Asmit ◽  
Syaiful Hadi
Keyword(s):  
Palm Oil ◽  
Time Series Data ◽  
Supply And Demand ◽  
Coconut Oil ◽  
Oil Prices ◽  
World Market ◽  
Least Square ◽  
Series Data ◽  
The World

ABSTRACT   Indonesia is the leading producer of palm oil in the world. In 2016 Indonesia and Malaysia produced 81% of the world's palm oil. This study aims to analyze the response of the supply and demand for Indonesian palm oil in the world market. This study used time-series data from 1980-2016. The model built is an econometric model, simultaneous equations. To answer the research objectives, the data were analyzed using the Two Stages Least Square (2SLS) method. The main finding of this study is that in the short term, there are no responsive variables. In the long term, the variable that is responsive to the supply of Indonesian palm oil is the lag area of Indonesian palm oil. In the Malaysian palm oil supply equation, the response variable is the lag area of Malaysian palm oil. In terms of domestic demand for Indonesian palm oil, there are no responsive variables both in the short and long term. In the equation of demand for Malaysian palm oil, the responsive variables are the price of Malaysian palm oil and the price of Malaysian coconut oil. In the international demand for palm oil, the responsive variables are the increase in world palm oil prices, world palm oil prices, 2-year lag in world palm oil prices, and GDP per capita Pakistan. In terms of price, the responsive variable affecting the price of Indonesian palm oil is the world price of palm oil.

scholarly journals An Assessment of the Determinants of Productivity in the Electricity Industry in Nigeria

2018 ◽  
Vol 14 (19) ◽  
pp. 256
Author(s):  
Olatunji, Olabode David
Keyword(s):  
Best Practice ◽  
Time Series Data ◽  
Weather Condition ◽  
Electricity Industry ◽  
Least Square ◽  
Electricity Sector ◽  
Series Data ◽  
Energy Information Administration ◽  
National Bureau ◽  
Transparency International

The study examined the productivity in the electricity industry in Nigeria. The aim of the study was to ascertain the determinants of productivity in the electricity sector. The research design adopted for the study was a longitudinal study of productivity in the electricity industry in Nigeria. The study considered time series data for a 20 year period from 1996 to 2015. Data on study variables were obtained from Central Bank of Nigeria (CBN) statistical bulletins, National Bureau of Statistics (NBS) annual publications, and the websites of both Transparency International (TI) and Energy Information Administration (EIA). Based on the study objectives, the fully modified ordinary least square (FM-OLS) technique was used to estimate the multiple regressions between productivity and the explanatory variables. Data analyses were carried out using the software application of E- View 9.0. Results from the study showed that the total factor productivity which is an indication of efficiency in the electricity sector was 0.29. This is low when compared with international best practice of 0.80. Also, results from the study revealed that funding, weather condition, vandalism and labour supply have significant effect on productivity of the electricity industry in Nigeria. However, tariff structure and corruption were not statistically significant in the prediction of productivity in the electricity industry. The study recommended that increased budgetary allocations should be made available to the electricity industry to provide the needed improvements in the sector.

scholarly journals Port Revenue Performance and Economic Growth: The Nigerian Ports Authority Experience, 2010-2019

2020 ◽  
Vol 11 (2) ◽  
pp. 1-11
Author(s):  
Richard C. Osadume ◽  
Edih O. University
Keyword(s):  
Economic Growth ◽  
Time Series Data ◽  
Least Square ◽  
Series Data ◽  
National Bureau ◽  
Short Run ◽  
Ordinary Least Square Regression ◽  
Level Of Significance ◽  
Cargo Throughput ◽  
Operating Surplus

AbstractThe Study examined Port Revenue Performance and Economic Growth: The Nigerian Ports Authority Experience, 2010 to 2019. The objective of this study is to examine the effect of Port Revenue Performance on Nigeria's economic growth by critically evaluating the Nigerian Ports Authority Performance. The neoclassical growth theory was employed in the study and the Nigeria Ports Authority was chosen as its sample, covering the period from 2010 to 2019. The study used secondary time series data sourced from the Nigeria Ports Authority and the National Bureau of Statistics and used the ordinary least square regression and the Engle-Granger co-integration to test the variables at the 5% level of significance. The findings showed that total revenue to gross registered tonnage had positive and significant effect on economic growth while operating surplus to operating revenue showed a negative but significant effect and operating surplus to cargo throughput showed insignificant effect; there was no co-integration between the variables. The study concludes that Port revenue performance affects economic growth in the short-run only, and it recommends amongst others that policy makers should formulate appropriate and implementable regulatory framework that will address infrastructural deficits at the ports and stimulate increased utilization by major foreign vessel companies.

Temporal trends of the association between extreme temperatures and hospitalisations for schizophrenia in Hefei, China from 2005 to 2014

2021 ◽  
Vol 78 (5) ◽  
pp. 364-370
Author(s):  
Rubing Pan ◽  
Qizhi Wang ◽  
Weizhuo Yi ◽  
Qiannan Wei ◽  
Jian Cheng ◽  
...  
Keyword(s):  
Time Series Data ◽  
Temporal Trends ◽  
Extreme Temperature ◽  
Series Data ◽  
Extreme Temperatures ◽  
Distributed Lag ◽  
Increasing Trend ◽  
Related Hospitalisation ◽  
Extreme Cold ◽  
And Gender

ObjectiveWe aimed to examine the temporal trends of the association between extreme temperature and schizophrenia (SCZ) hospitalisations in Hefei, China.MethodsWe collected time-series data on SCZ hospitalisations for 10 years (2005–2014), with a total of 36 607 cases registered. We used quasi-Poisson regression and distributed lag non-linear model (DLNM) to assess the association between extreme temperature (cold and heat) and SCZ hospitalisations. A time-varying DLNM was then used to explore the temporal trends of the association between extreme temperature and SCZ hospitalisations in different periods. Subgroup analyses were conducted by age (0–39 and 40+ years) and gender, respectively.ResultsWe found that extreme cold and heat significantly increased the risk of SCZ hospitalisations (cold: 1st percentile of temperature 1.19 (95% CI 1.04 to 1.37) and 2.5th percentile of temperature 1.16 (95% CI 1.03 to 1.31); heat: 97.5th percentile of temperature 1.37 (95% CI 1.13 to 1.66) and 99th percentile of temperature 1.38 (95% CI 1.13 to 1.69)). We found a slightly decreasing trend in heat-related SCZ hospitalisations and a sharp increasing trend in cold effects from 2005 to 2014. However, the risk of heat-related hospitalisation has been rising since 2008. Stratified analyses showed that age and gender had different modification effects on temporal trends.ConclusionsThe findings highlight that as temperatures rise the body’s adaptability to high temperatures may be accompanied by more threats from extreme cold. The burden of cold-related SCZ hospitalisations may increase in the future.

scholarly journals Import Flows of Bangladesh: Gravity Model Approach under Panel Data Methodology

2012 ◽  
Vol 60 (2) ◽  
pp. 153-157 ◽  
Author(s):  
Mili Roy ◽  
Md. Israt Rayhan
Keyword(s):  
Panel Data ◽  
Gravity Model ◽  
Cross Section ◽  
Time Series Data ◽  
Random Effect ◽  
Least Square ◽  
Series Data ◽  
Ordinary Least Square ◽  
Extended Gravity ◽  
Trading Partners

In counterpoint to export growth, Bangladesh import growth has remained much less strong, despite impressive progress in import liberalization. This study gives an overview of different methodologies related to gravity model analysis in Bangladesh’s import flow. A pooled cross section and time series data were analyzed to incorporate the country specific heterogeneity in country pair trading partners. The import flows are justified by the basic gravity model since Bangladesh’s imports are positively significant by the economy size and inversely related to trade barrier. Accordingly, we have analyzed pooled ordinary least square, fixed effect, random effect. This study also explores extended gravity model using several variables in the light of gravity model panel data approach. Bangladesh’s import is determined by the home and foreign country’s gross domestic product and exchange rate. In addition, Cross section results show that regional trade arrangement which is South Asian Association for Regional Co-operation and border are significant for Bangladesh’s importimplies that Bangladesh should import more from intra regional country and also should import from India.DOI: http://dx.doi.org/10.3329/dujs.v60i2.11485 Dhaka Univ. J. Sci. 60(2): 153-157, 2012 (July)  

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