scholarly journals Measuring Advertising Expenditure Effects on the Nigerian Economy

2020 ◽  
Vol 3 (3) ◽  
pp. 80-93
Author(s):  
Shafiu Ibrahim Abdullahi ◽  
Shuaibu Mukhtar
Keyword(s):  
High Frequency ◽  
Time Series Data ◽  
Developing Economies ◽  
Series Data ◽  
Advertising Expenditure ◽  
Scope For Growth ◽  
Macroeconomic Variables ◽  
Business Units ◽  
Advanced Economies ◽  
State Of The Economy

This study explores relationships between annual advertising expenditure and major macroeconomic variables in Nigeria. Advertising is sometimes viewed as a concern of business units only not worth being researched at macroeconomic level. This nature has been mostly studied on advertising industries in the advanced economies. Due to a lack of high frequency time series data on advertising expenditure in the developing economies, this work has been limited to an exploratory study using the multiple regression and correlation analysis. The study covers the period of 2001 to 2018. Its findings show that advertising has positive relationship with GDP and savings. This study provides further evidence on the cyclical nature of advertising that moves with the state of the economy. During the economic slowdown in the period of 2015 to 2017, Nigeria advertising expenditure continued to fall. In 2013, the period with the highest advertising revenue in the study, the ratio of advertising expenditure as percentage of GDP accounted for 0.061%, which was below 0.2%, a very negligible number indicating more scope for growth in the market.

scholarly journals The Impact of Macroeconomic Factors on Stock Market: An Evidence from China and Pakistan

2020 ◽  
pp. 1-26
Author(s):  
Isbat Alam ◽  
Muhammad Mohsin ◽  
Khalid Latif ◽  
Muhammad Zia-ur -Rehman
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Developing Economies ◽  
Stock Exchange ◽  
Series Data ◽  
Foreign Direct Investments ◽  
Stock Market Returns ◽  
Macroeconomic Variables ◽  
The Government ◽  
The Impact

Silk Road is an ancient strategy of economic and trade routes development networks between emerging and developing economies (China & Pakistan). The main purpose of this research is to empirical inspect the association that exists among the China stock exchange (SSE), Pakistan Stock Exchange (KSE-100) with macroeconomic variables (Gross Domestic Product, Balance of Trade, Foreign Direct Investments, Lending interest rate, and Money Supply). The annual time series data from 1995 to 2019 used to find out the results. Macroeconomic variables have an essential role in any changes in every economy. Any unexpected variations amongst these variables influence the economy in several ways. Multiple regression techniques were analyzed and examine for the significance of data to approximate the probable impacts of variables on stock market prices. Breusch Godfrey Serial Correlation with heteroskedasticity assessment is utilized to investigate the correctness as well as residual normality of series data. The finding of this study exposed that GDP is negative significant 10% with SSE and 1% at level with KSE, FDI is insignificant with SSE. negative significant 10% at level with KSE and the result of BOT shows positive significant 5% at level with SSE while insignificant with KSE, M2 is significant 5% at level with SSE but insignificant with KSE and LI are shown statistically significant 1% at level with SSE While positive significant 10% with KSE. It is determined that it is significant and an insignificant relationship among the variables with both stock market returns. The financial analyst, policymaker appreciate these findings, investors, shareholder, stock exchange editors, security exchange supervisors as well as for the Government.                                                                                          

Testing Structural Break in the Relationship Between Exchange Rate and Macroeconomic Variables

2019 ◽  
Vol 23 (4) ◽  
pp. 442-453 ◽  
Author(s):  
Saidia Jeelani ◽  
Joity Tomar ◽  
Tapas Das ◽  
Seshanwita Das
Keyword(s):  
Exchange Rate ◽  
Structural Breaks ◽  
Time Series Data ◽  
Structural Break ◽  
Series Data ◽  
Ripple Effect ◽  
Macroeconomic Factors ◽  
Parameter Instability ◽  
Macroeconomic Variables ◽  
The Relationship

The article aims to study the relationship between those macroeconomic factors that the affect (INR/USD) exchange rate (ER). Time series data of 40 years on ER, GDP, inflation, interest rate (IR), FDI, money supply, trade balance (TB) and terms of trade (ToT) have been collected from the RBI website. The considered model has suggested that only inflation, TB and ToT have influenced the ER significantly during the study period. Other macroeconomic variables such as GDP, FDI and IR have not significantly influenced the ER during the study period. The model is robust and does not suffer from residual heteroscedasticity, autocorrelation and non-normality. Sometimes the relationship between ER and macroeconomic variables gets affected by major economic events. For example, the Southeast Asian crisis caused by currency depreciation in 1997 and sub-prime loan crisis of 2008 severely strained the national economies. Any global economic turmoil will affect different economic variables through ripple effect and this, in turn, will affect the ER of different economies differently. The article has also diagnosed whether there is any structural break or not in the model by applying Chow’s Breakpoint Test and have obtained multiple breaks between 2003 and 2009. The existence of structural breaks during 2003–2009 is explained by the fact that volume of crude oil imported by India is high and oil price rise led to a deficit in the TB alarmingly, which caused a structural break or parameter instability.

scholarly journals The long-Run and Short-Run Analysis between Stock Market Index and Macroeconomic Variables in Jordan: Bounds Tests Approach

2019 ◽  
Vol 12 (4) ◽  
pp. 50
Author(s):  
Raed Walid Al-Smadi ◽  
Muthana Mohammad Omoush
Keyword(s):  
Stock Market ◽  
Time Series Data ◽  
Stock Exchange ◽  
Series Data ◽  
Stock Market Index ◽  
Macroeconomic Variables ◽  
Market Index ◽  
Long Run ◽  
Equilibrium Relationship ◽  
Short Run

This paper investigates the long-run and short-run relationship between stock market index and the macroeconomic variables in Jordan. Annual time series data for the 1978–2017 periods and the ARDL bounding test are used. The results identify long-run equilibrium relationship between stock market index and the macroeconomic variables in Jordan. Jordanian policy makers have to pay more attention to the current regulation in the Amman Stock Exchange(ASE) and manage it well, thus ultimately helping financial development.

scholarly journals The impact of bank-specific and macroeconomic variables on profitability of Islamic rural bank in Indonesia

2019 ◽  
Vol 5 (3) ◽  
Author(s):  
Muhammad Sanusi
Keyword(s):  
Banking Sector ◽  
Time Series Data ◽  
Series Data ◽  
Estimation Model ◽  
Policy Makers ◽  
Vector Error Correction ◽  
Macroeconomic Variables ◽  
Vector Error ◽  
The Impact

This paper investigates the impact of bank-specific and macroeconomic variables on the profitability of Islamic rural bank (BPRS) in Indonesia. Using monthly time series data from January 2010 - December 2018. The estimation model used is a vector error correction model to analyze the long-term and short-term relationships between bank-specific and macroeconomic variables on the profitability of Islamic rural bank. The results showed that CAR and LnTA had a significant positive relationship, while NPF, BOPO and IPI had a negative and significant relationship to the profitability of Islamic rural banks. But FDR and Inflation variables are not significantly related to the profitability of Islamic rural bank. The results leave implications for policy makers, investors and banking sector managers. Based on evidence that bank profitability is more influenced by internal banks (as specific as banks), this research can help Islamic rural banks to help them understand which factors are important to be analyzed to obtain higher profitability.

scholarly journals A New Method to Detect Outliers in High-frequency Time Series

2018 ◽  
Vol 8 (1) ◽  
pp. 16
Author(s):  
Ilaria Lucrezia Amerise ◽  
Agostino Tarsitano
Keyword(s):  
Time Series ◽  
High Frequency ◽  
Time Series Data ◽  
New Method ◽  
Series Data ◽  
Absolute Difference ◽  
Data Preparation ◽  
Simple Method ◽  
Pass Through ◽  
Nonparametric Procedure

The objective of this research is to develop a fast, simple method for detecting and replacing extreme spikes in high-frequency time series data. The method primarily consists  of a nonparametric procedure that pursues a balance between fidelity to observed data and smoothness. Furthermore, through examination of the absolute difference between original and smoothed values, the technique is also able to detect and, where necessary, replace outliers with less extreme data. Unlike other filtering procedures found in the literature, our method does not require a model to be specified for the data. Additionally, the filter makes only a single pass through the time series. Experiments  show that the new method can be validly used as a data preparation tool to ensure that time series modeling is supported by clean data, particularly in a complex context such as one with high-frequency data.

Time Series Data Analysis by Ultra-High Frequency Trigonometric Higher Order Neural Networks

2021 ◽  
pp. 218-261
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Exchange Rates ◽  
High Frequency ◽  
Time Series Data ◽  
Higher Order ◽  
Series Data ◽  
Ultra High Frequency ◽  
Higher Order Neural Networks ◽  
Time Series Data Analysis

This chapter develops a new nonlinear model, ultra high frequency trigonometric higher order neural networks (UTHONN) for time series data analysis. UTHONN includes three models: UCSHONN (ultra high frequency sine and cosine higher order neural networks) models, UCCHONN (ultra high frequency cosine and cosine higher order neural networks) models, and USSHONN (ultra high frequency sine and sine higher order neural networks) models. Results show that UTHONN models are 3 to 12% better than equilibrium real exchange rates (ERER) model, and 4–9% better than other polynomial higher order neural network (PHONN) and trigonometric higher order neural network (THONN) models. This study also uses UTHONN models to simulate foreign exchange rates and consumer price index with error approaching 10-6.

scholarly journals WHICH VARIABLES PREDICT INDONESIA'S INFLATION?

2019 ◽  
Vol 22 (1) ◽  
pp. 87-102 ◽  
Author(s):  
Susan Sunila Sharma
Keyword(s):  
Time Series ◽  
Comparative Analysis ◽  
Inflation Rate ◽  
Time Series Data ◽  
Predictor Variables ◽  
Series Data ◽  
Macroeconomic Variables ◽  
Monthly Time Series ◽  
Out Of Sample ◽  
Exhaustive List

We use an exhaustive list of Indonesia’s macroeconomic variables in a comparative analysis to determine which predictor variables are most important in forecasting Indonesia’s inflation rate. We use monthly time-series data for 30 macroeconomic variables. Using both in-sample and out-of-sample predictability evaluations, we report consistent evidence of inflation rate predictability using 11 out of 30 macroeconomic variables.

scholarly journals Growth Governance Nexus: A Case of Pakistan

2013 ◽  
Vol 5 (8) ◽  
pp. 562-572
Author(s):  
Rabia Nazir ◽  
Mumtaz Anwar .
Keyword(s):  
Time Series Data ◽  
Good Governance ◽  
Developing Economies ◽  
Series Data ◽  
Gdp Growth ◽  
Development Agenda ◽  
Tremendous Importance ◽  
Free Media ◽  
Political Economic

Good governance has gained tremendous importance in the development agenda of developing economies since 1990s but growth literature gives mixed picture about the role of governance and institutional factors in explaining GDP growth. The present study is an attempt to provide empirical evidence on interlinks between governance and GDP growth. ADF and Johansen co-integration tests are applied for econometric testing of the hypothesis by using time series data from 1984 to 2010. All the variables turned out to be significant with ICRG (proxy used for governance) having positive and significant impact on GDP growth of Pakistan. Results of the study have shown that governance plays major role in determining GDP growth pattern of Pakistan. A complete reform of the political, economic system, judiciary, bureaucracy and a free media are recommended to improve governance and to achieve sustained GDP growth in Pakistan consequently.

scholarly journals Investment Incentives as a Mediator in the Relationship between Macroeconomic Variables and Growth of Private Domestic Investment in Kenya

2021 ◽  
pp. 1-14
Author(s):  
Monica Wanjiru Kinyanjui ◽  
Willy Muturi ◽  
Agnes Njeru
Keyword(s):  
Time Series Data ◽  
Mediating Effect ◽  
Series Data ◽  
Investment Incentives ◽  
Domestic Investment ◽  
Macroeconomic Variables ◽  
Step Procedure ◽  
Tax Expenditure ◽  
Mediation Hypothesis ◽  
The Relationship

The objective of this study was to investigate the mediating effect of investment incentives on the growth of private domestic investment in Kenya using time series data for the period 1997 to 2018. To test for mediating effect, the study used (Baron & Kenny, 1986) approach which propose a four-step procedure in which several regression analyses were conducted and the significance of the coefficients examined. The results did not consistently support a full mediation hypothesis, given that the coefficients did not consistently change in magnitude and significance. Therefore, the study does not reject the null hypothesis that investment incentives do not meditate on the relationship between macroeconomic variables and the growth of private domestic investment in Kenya. The results of this study will benefit policy makers by providing them with data-based evidence that will guide them in making appropriate policies that encourage growth of private domestic investment in Kenya and institute proper management of private domestic investments to boost economic growth in Kenya. Keywords: Tax expenditure, Investment tax expenditure, Investment tax credit, Private domestic investment.

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