Rescuing Nigeria’s Tobacco Industry: A Battle between Life and Death

2020 ◽  
pp. 46-57
Keyword(s):  
Value Chain ◽  
Time Series Data ◽  
Series Data ◽  
Cash Crop ◽  
Life And Death ◽  
Oil Boom ◽  
Cash Crops ◽  
Producer Prices ◽  
Production Area ◽  
The Impact

Tobacco commodity is among the potential cash crops which supported the economy of the country before the oil boom. For almost a decade, the impact of the neglect of this cash crop is affecting the nation’s revenue as the mono-economy of the country is being marred by dwindling oil prices, thus affecting the country’s balance of payment annually. It is against this background that empirical research which will bring-out the measures needed to salvage the sub-sector (tobacco) was conceptualized. Time series data sourced from the FAO database that ranged from 1961 to 2017; covering production, area, yield and producer prices were used. Both descriptive and inferential statistics were used to analyze the data. The empirical evidence showed the performance of tobacco production in the country to be poor through the regime periods which marked the nation’s economy. Poor policy, production, technological, and marketing risks were the pronounced factors that inhibited the performance of the cash crop in the country. Furthermore, the future of this cash crop is not promising as the annual output will be plummeting due majorly to production and technological risks. Therefore, the need to revive this sub-sector viz. provision of production finance and establishment of a viable marketing value chain by the policymakers becomes inevitable as cash crops are the only alternative that will stabilize the nation’s economy because it is obvious that crude oil will not be able to sustain Nigerian economy.

A Macroeconomic Analysis of Agricultural Sector in Nigeria

2019 ◽  
Vol 5 (1) ◽  
pp. 18-25
Author(s):  
Isah Funtua Abubakar ◽  
Umar Bambale Ibrahim
Keyword(s):  
Value Chain ◽  
Crop Production ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Tourism Industry ◽  
Series Data ◽  
Size Analysis ◽  
The Real ◽  
Real Gdp ◽  
The Impact

This paper attempts to study the Nigerian agriculture industry as a panacea to growth as well as an anchor to the diversification agenda of the present government. To do this, the time series data of the four agriculture subsectors of crop production, livestock, forestry and fishery were analysed as stimulus to the Real GDP from 1981-2016 in order to explicate the individual contributions of the subsectors to the RGDP in order to guide the policy thrust on diversification. Using the Johansen approach to cointegration, all the variables were found to be cointegrated. With the exception of the forestry subsector, all the three subsectors were seen to have impacted on the real GDP at varying degrees during the time under review. The crop production subsector has the highest impact, however, taking size-by-size analysis, the livestock subsector could be of much importance due to its ability to retain its value chain and high investment returns particularly in poultry. Therefore, it is recommended that, the government should intensify efforts to retain the value chain in the crop production subsector, in order to harness its potentials optimally through the encouragement of the establishment of agriculture cottage industries. Secondly, the livestock subsector is found to be the most rapidly growing and commercialized subsector. Therefore, it should be the prime subsector to hinge the diversification agenda naturally. Lastly, the tourism industry which is a source through which the impact of the subsector is channeled to the GDP should be developed, in order to improve the impact of such channel to GDP with the sole objective to resuscitate the forestry subsector.

Technology Exports and Global Value Chain Linkages: A Comparative Sectoral Study of India

2020 ◽  
Vol 68 (1) ◽  
pp. 8-28
Author(s):  
Kashika Arora ◽  
Areej Aftab Siddiqui
Keyword(s):  
Granger Causality ◽  
Value Chain ◽  
Time Series Data ◽  
Export Performance ◽  
Series Data ◽  
High Tech ◽  
Comparative Performance ◽  
Long Run ◽  
Short Run ◽  
The Impact

Technology being incorporated in products, intermediate inputs and processes varies from sector to sector. Using annual time series data (1991–2017), a comparative performance of two sectors, namely, a high-tech (electronics and hardware) and low-tech (textiles and clothing), is undertaken to elaborate on the linkages between trade and technology. The empirical analysis in the form of auto regressive distributive lag (ARDL) testing approach to co-integration concludes that there is strong evidence of positive long-run relationship between extensive margin, gross fixed capital formation and revealed comparative advantage (RCA) with gross exports (GE) for the textile and clothing sector. Also, there runs a bidirectional Granger causality between RCA and GE and unidirectional Granger causality from GE to extensive and intensive margins and production value. However, there is a lack of evidence of long-run co-integration in the electronics sector. Still, a short-run positive causal relationship exists between lagged values of GE, intensive margin and production with GE. Together, the impact of these variables on the sector’s export performance varies, thus posing a challenge as well as providing a direction for the policies to reap further from this potential nexus of trade, investment and global value chains.

scholarly journals Impact of Government Expenditure on Agricultural Value Chain in Nigeria

2020 ◽  
pp. 192-204
Author(s):  
Eneji Mathias Agri ◽  
Agri Angela Iyaji ◽  
Felix Nanwul Diyemang ◽  
Offorma Jecinta Chioma
Keyword(s):  
Value Chain ◽  
Positive Relationship ◽  
Agricultural Sector ◽  
Time Series Data ◽  
Government Expenditure ◽  
Percent Level ◽  
Ordinary Least Squares ◽  
Series Data ◽  
Huge Impact ◽  
The Impact

This research examined the impact of government expenditure on agricultural value chain in Nigeria. It uses annual time series data for the period 1998-2018. Statistical Techniques, survey, simple percentages and the Ordinary Least Squares (OLS) methods were adopted. The OLS result using Multiple Regression analysis revealed an insignificant positive relationship between government expenditure and Agricultural value chain, proxy by Aggregate importation of rice (AMR). Imports had a negative sign; it is a leakage on the economy. It however, showed that agricultural gross domestic product (ADP) has a positive relationship with government expenditure, at 5 percent level. The pair-wise Granger causality tests showed that government expenditure on agriculture (GEA) granger causes aggregate importation of rice (AMR), this was indicated by their respective F-statistics and probability values which stood at 0.39420(0.6815).. In conclusion, government expenditure, with supportive policies, would have huge impact on agricultural value chain in Nigeria. The agricultural sector is the engine of economic recovery, growth and development, therefore an improvement in government spending to the sector is recommended. This study contributes to the downstream linkages in the agricultural sector.

Impact of exchange rate and oil price on the yield of sovereign bond and sukuk: Evidence from Malaysian capital market

2017 ◽  
Vol 5 (4) ◽  
pp. 27
Author(s):  
Huda Arshad ◽  
Ruhaini Muda ◽  
Ismah Osman
Keyword(s):  
Exchange Rate ◽  
Capital Market ◽  
Time Series Data ◽  
Oil Prices ◽  
Oil Price ◽  
Series Data ◽  
Sovereign Bond ◽  
Long Run ◽  
Short Run ◽  
The Impact

This study analyses the impact of exchange rate and oil prices on the yield of sovereign bond and sukuk for Malaysian capital market. This study aims to ascertain the effect of weakening Malaysian Ringgit and declining of crude oil price on the fixed income investors in the emerging capital market. This study utilises daily time series data of Malaysian exchange rate, oil price and the yield of Malaysian sovereign bond and sukuk from year 2006 until 2015. The findings show that the weakening of exchange rate and oil prices contribute different impacts in the short and long run. In the short run, the exchange rate and oil prices does not have a direct relation with the yield of sovereign bond and sukuk. However, in the long run, the result reveals that there is a significant relationship between exchange rate and oil prices on the yield of sovereign bond and sukuk. It is evident that only a unidirectional causality relation is present between exchange rate and oil price towards selected yield of Malaysian sovereign bond and sukuk. This study provides numerical and empirical insights on issues relating to capital market that supports public authorities and private institutions on their decision and policymaking process.

Transport infrastructure of the Rostov Oblast: Problems and prospects for development in the context of national projects implementation

2020 ◽  
Vol 19 (6) ◽  
pp. 1015-1034
Author(s):  
O.Yu. Patrakeeva
Keyword(s):  
Time Series Data ◽  
Mutual Influence ◽  
Rostov Oblast ◽  
Transport Infrastructure ◽  
Series Data ◽  
Cointegration Tests ◽  
Level Of Economic Development ◽  
Short Run ◽  
The Government ◽  
The Impact

Subject. The paper considers national projects in the field of transport infrastructure, i.e. Safe and High-quality Roads and Comprehensive Plan for Modernization and Expansion of Trunk Infrastructure, and the specifics of their implementation in the Rostov Oblast. Objectives. The aim is to conduct a statistical assessment of the impact of transport infrastructure on the region’s economic performance and define prospects for and risks of the implementation of national infrastructure projects in conditions of a shrinking economy. Methods. I use available statistics and apply methods and approaches with time-series data, namely stationarity and cointegration tests, vector autoregression models. Results. The level of economic development has an impact on transport infrastructure in the short run. However, the mutual influence has not been statistically confirmed. The paper revealed that investments in the sphere of transport reduce risk of accidents on the roads of the Rostov Oblast. Improving the quality of roads with high traffic flow by reducing investments in the maintenance of subsidiary roads enables to decrease accident rate on the whole. Conclusions. In conditions of economy shrinking caused by the complex epidemiological situation and measures aimed at minimizing the spread of coronavirus, it is crucial to create a solid foundation for further economic recovery. At the government level, it is decided to continue implementing national projects as significant tools for recovery growth.

The Effects of Oil Prices Changes on Output Growth and Inflation: Evidence from Turkey

2013 ◽  
Vol 5 (11) ◽  
pp. 730-739 ◽  
Author(s):  
Pelin ÖGE GÜNEY
Keyword(s):  
Time Series Data ◽  
Output Growth ◽  
Oil Price ◽  
Series Data ◽  
Negative Effects ◽  
Price Changes ◽  
Asymmetric Effects ◽  
Price Increases ◽  
Causality Tests ◽  
The Impact

This paper investigates the effects of oil price changes on output and inflation for the case of Turkey using monthly time series data for the period 1990:1–2012:3. Recent studies suggest that oil price changes may have asymmetric effects on the macroeconomic variables. To account for asymmetric effects, we decompose oil price changes into positive and negative parts following Hamilton (1996). Our results show that while oil price increases have clear negative effects on output growth, the impact of oil price decline is insignificant. Similarly, oil price increases have positive and significant effects on inflation. However, oil price declines have not a significant effect on inflation. The Granger causality tests also support these results.

Does Tax Increment Financing Pass the “But-for” Test in Missouri?

2019 ◽  
Vol 33 (3) ◽  
pp. 187-202
Author(s):  
Ahmed Rachid El-Khattabi ◽  
T. William Lester
Keyword(s):  
Economic Development ◽  
Kansas City ◽  
Time Series Data ◽  
Local Level ◽  
Conclusive Evidence ◽  
Series Data ◽  
Tax Increment Financing ◽  
Data Set ◽  
Development Indicators ◽  
The Impact

The use of tax increment financing (TIF) remains a popular, yet highly controversial, tool among policy makers in their efforts to promote economic development. This study conducts a comprehensive assessment of the effectiveness of Missouri’s TIF program, specifically in Kansas City and St. Louis, in creating economic opportunities. We build a time-series data set starting 1990 through 2012 of detailed employment levels, establishment counts, and sales at the census block-group level to run a set of difference-in-differences with matching estimates for the impact of TIF at the local level. Although we analyze the impact of TIF on a wide set of indicators and across various industry sectors, we find no conclusive evidence that the TIF program in either city has a causal impact on key economic development indicators.

EFFECTS OF TREND AND PERIODICITY ON THE CORRELATION DIMENSION AND THE LYAPUNOV EXPONENTS

2008 ◽  
Vol 18 (12) ◽  
pp. 3679-3687 ◽  
Author(s):  
AYDIN A. CECEN ◽  
CAHIT ERKAL
Keyword(s):  
Time Series ◽  
Lyapunov Exponent ◽  
Lyapunov Exponents ◽  
Correlation Dimension ◽  
Time Series Data ◽  
Logistic Map ◽  
Model Identification ◽  
Series Data ◽  
Largest Lyapunov Exponent ◽  
The Impact

We present a critical remark on the pitfalls of calculating the correlation dimension and the largest Lyapunov exponent from time series data when trend and periodicity exist. We consider a special case where a time series Zi can be expressed as the sum of two subsystems so that Zi = Xi + Yi and at least one of the subsystems is deterministic. We show that if the trend and periodicity are not properly removed, correlation dimension and Lyapunov exponent estimations yield misleading results, which can severely compromise the results of diagnostic tests and model identification. We also establish an analytic relationship between the largest Lyapunov exponents of the subsystems and that of the whole system. In addition, the impact of a periodic parameter perturbation on the Lyapunov exponent for the logistic map and the Lorenz system is discussed.

scholarly journals A Comparison of Time-Series Predictions for Healthcare Emergency Department Indicators and the Impact of COVID-19

2021 ◽  
Vol 11 (8) ◽  
pp. 3561
Author(s):  
Diego Duarte ◽  
Chris Walshaw ◽  
Nadarajah Ramesh
Keyword(s):  
Time Series ◽  
Time Series Data ◽  
Moving Average ◽  
General Regression Neural Network ◽  
Series Data ◽  
Machine Learning Model ◽  
Hospital Patients ◽  
Major Incidents ◽  
General Regression ◽  
The Impact

Across the world, healthcare systems are under stress and this has been hugely exacerbated by the COVID pandemic. Key Performance Indicators (KPIs), usually in the form of time-series data, are used to help manage that stress. Making reliable predictions of these indicators, particularly for emergency departments (ED), can facilitate acute unit planning, enhance quality of care and optimise resources. This motivates models that can forecast relevant KPIs and this paper addresses that need by comparing the Autoregressive Integrated Moving Average (ARIMA) method, a purely statistical model, to Prophet, a decomposable forecasting model based on trend, seasonality and holidays variables, and to the General Regression Neural Network (GRNN), a machine learning model. The dataset analysed is formed of four hourly valued indicators from a UK hospital: Patients in Department; Number of Attendances; Unallocated Patients with a DTA (Decision to Admit); Medically Fit for Discharge. Typically, the data exhibit regular patterns and seasonal trends and can be impacted by external factors such as the weather or major incidents. The COVID pandemic is an extreme instance of the latter and the behaviour of sample data changed dramatically. The capacity to quickly adapt to these changes is crucial and is a factor that shows better results for GRNN in both accuracy and reliability.

scholarly journals Assessing Stream-Aquifer Connectivity in a Coastal California Watershed

Water ◽  
2021 ◽  
Vol 13 (4) ◽  
pp. 416
Author(s):  
Bwalya Malama ◽  
Devin Pritchard-Peterson ◽  
John J. Jasbinsek ◽  
Christopher Surfleet
Keyword(s):  
Time Series ◽  
Spectral Analysis ◽  
Water Level ◽  
Time Series Data ◽  
Series Data ◽  
Low Permeability ◽  
Pumping Tests ◽  
Stream Flows ◽  
The Impact

We report the results of field and laboratory investigations of stream-aquifer interactions in a watershed along the California coast to assess the impact of groundwater pumping for irrigation on stream flows. The methods used include subsurface sediment sampling using direct-push drilling, laboratory permeability and particle size analyses of sediment, piezometer installation and instrumentation, stream discharge and stage monitoring, pumping tests for aquifer characterization, resistivity surveys, and long-term passive monitoring of stream stage and groundwater levels. Spectral analysis of long-term water level data was used to assess correlation between stream and groundwater level time series data. The investigations revealed the presence of a thin low permeability silt-clay aquitard unit between the main aquifer and the stream. This suggested a three layer conceptual model of the subsurface comprising unconfined and confined aquifers separated by an aquitard layer. This was broadly confirmed by resistivity surveys and pumping tests, the latter of which indicated the occurrence of leakage across the aquitard. The aquitard was determined to be 2–3 orders of magnitude less permeable than the aquifer, which is indicative of weak stream-aquifer connectivity and was confirmed by spectral analysis of stream-aquifer water level time series. The results illustrate the importance of site-specific investigations and suggest that even in systems where the stream is not in direct hydraulic contact with the producing aquifer, long-term stream depletion can occur due to leakage across low permeability units. This has implications for management of stream flows, groundwater abstraction, and water resources management during prolonged periods of drought.

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