Vector Autoregression Techniques Research Articles

Medium- and Long-Term Prediction of Polar Motion Using Weighted Least Squares Extrapolation and Vector Autoregressive Modeling

ABSTRACT This article presents the application of weighted least squares (WLS) extrapolation and vector autoregressive (VAR) modeling in polar motion prediction. A piecewise weighting function is developed for the least squares (LS) adjustment in consideration of the effect of intervals between observation and prediction epochs on WLS extrapolation. Furthermore, the VAR technique is used to simultaneously model and predict the residuals of x p, y p pole coordinates for WLS misfit. The simultaneous predictions of x p, y p pole coordinates are subsequently computed by the combination of WLS extrapolation of harmonic models for the linear trend, Chandler and annual wobbles, and VAR stochastic prediction of the residuals (WLS+VAR). The 365-day-ahead x p, y p predictions are compared with those generated by LS extrapolation+univariate AR prediction and LS extrapolation+VAR modeling. It is shown that the x p, y p predictions based on WLS+VAR taking into consideration both the interval effect and correlation between x p and y p outperform those generated by two others. The accuracies of the x p predictions are 13.97 mas, 18.47 mas, and 20.52 mas, respectively for the 150-, 270-, and 365-day horizon in terms of the mean absolute error statistics, 36%, 24.8%, and 33.5% higher than LS+AR, respectively. For the y p predictions, the 150-, 270-, and 365-day accuracies are 15.41 mas, 21.17 mas, and 21.82 mas respectively, 27.4%, 11.9%, and 21.8% higher than LS+AR respectively. Moreover, the absolute differences of the WLS+VAR predictions and observations are smaller than the differences from LS+VAR and LS+AR, which is practically important to practical and scientific users, although the improvement in accuracies is no more than 10% relative to LS+VAR. The further comparison with the predictions submitted to the 1st Earth Orientation Parameters Prediction Comparison Campaign (1st EOP PCC) shows that while the accuracy of the predictions within 30 days is comparable with that by the most accurate prediction techniques including neural networks and LS+AR participating in the campaign for x p, y p pole coordinates, the accuracy of the predictions up to 365 days into the future are better than accuracies by the other techniques except best LS+AR used in the EOP PCC. It is therefore concluded that the medium- and long-term prediction accuracy of polar motion can be improved by modeling x p, y p pole coordinates together.

Anaysis of Interest Rate Spread, Financial Development and Foreign Capital Inflow Nexus in Nigeria

ABSTRACT: The world has gone through various economic crises in the past century, and their effects have had varying implications on the economies of countries all over the world. In a bid to help stabilise economies all over the world, various measures have been put in place. Some of these measures include regulations and policies by the Bretton Woods institutions (World Bank and International Monetary Fund) and their agencies. The idea behind these measures is to ensure sustainable growth and development among member states and other countries of the world. Some of these policies include the privatization and liberalization policies of the Bretton Woods institutions as well as other policies bordering on such economic and social benefits for people all over the world. The Nigerian economy in our contemporary time can be described as passing through a rather 'volatile' phase with respect to interest rate, financial development and foreign capital inflow. Thus, this study investigated the impact of interest rate spread and financial development on foreign capital inflow in Nigeria. Several studies have been carried out using different methodologies, such as; co-integration equation, multivariate vector auto regressive (VAR) model and vector error correction technique. Each methodology used was in line with the objective of the research in question. However, to achieve its objective, this paper adopted the Classical Linear Regression Model. The results of the study showed that financial development has a positive impact on foreign capital inflow, while interest rate spread on the other hand, was also found to have a positive impact on foreign capital inflow. Other control variables such as market capitalization and treasury bills rate were also found to positively affect foreign capital inflow, while the all share index had a negative impact on foreign capital inflow. Some economists have opined that the Nigerian economy is currently going through a phase of recession. In order for large scale investments to be made within the country, there is a need for foreign participants to be attracted to the Nigerian economy and pull their resources, both financial and non-financial into the country (but, not without regulation). However, for these investors to have confidence to make investments in the Nigerian economy, there has to be a high degree of economic stability in the country. This can be supported by enacting and implementing policies that can enhance the quality of interest rates spread and financial development within the country. The policy implication here involves enhancing financial development through sound policies and adopting competitive interest rates, could increase the rate of foreign inflow into the economy. In view of this, it is also recommended that government policies should target interest rate competitiveness, financial and economic development as well as sustainability.

Did raising doing business scores boost GDP?

We use the time series variation in the World Bank’s “distance to frontier” estimates of the ease of doing business to assess the effects of changes in this variable on real GDP per capita. The use of Vector Autoregression techniques allows us to identify shocks to the Doing Business scores that are initially uncorrelated with GDP, thus addressing an important endogeneity problem that affects the cross-sectional literature on this topic. We report a robust finding that improvements in Doing Business scores have at least a temporary negative impact on GDP and find little evidence for a positive effect in the years following these improvements.

Reservoir computing based on solitary-like waves dynamics of liquid film flows: A proof of concept

Several theoretical works have shown that solitons —waves that self-maintain constant shape and velocity as they propagate— can be used as a physical computational reservoir, a concept where machine learning algorithms designed for digital computers are replaced by analog physical systems that exhibit nonlinear dynamical behaviour. Here we propose and experimentally validate a novel reservoir computing (RC) system that for the first time employs solitary-like (SL) waves propagating on the surface of a liquid film flowing over an inclined surface. We demonstrate the ability of the SL wave RC system (SLRC) to forecast chaotic time series, also producing experimental evidence of the possibility to combine RC with nonlinear vector autoregression techniques not only in a computer program but also in a physical system.

A VAR Based Study on Energy Consumption and Economic Growth

Economic growth and energy consumption are interrelated for an economy and these variables are expected to indicate a positive correlation. This relationship has been probed in the study in the context of the United Arab Emirates for the time period 1996-2020. The study uses basic regression and Vector Auto Regression techniques for analysis. The study found that energy consumption and non-renewable energy consumption are positively correlated, are dependent on the country’s economic growth and this relationship is optimum at a lag of 7 years.

Is the floating exchange rate a shock absorber in Albania? Evidence from SVAR models

The choice of a foreign exchange regime hinges primarily on whether the real exchange rate acts as a shock absorber or reverberator for macroeconomic fluctuations. This policy choice is considered central especially prior to joining currency areas such as the Eurozone. We investigate whether Albania’s current floating exchange rate regime contributes to macroeconomic stability, or generates volatility. Using three different structural vector autoregression techniques, and an expanded five-variable model, we show that the real exchange rate has played a shock absorbing role, buffering the Albanian economy primarily from real demand shocks. The analysis reveals that monetary shocks and supply-side shocks have modest contributions in real exchange rate volatility. This evidence in favor of the “shock absorbing” view of exchange rates lends support to Albania’s policy choice of a flexible exchange rate system. If in future Albania considers joining a currency area, its monetary authority will need to pay attention to real currency misalignments as well as the availability and flexibility of alternative adjustment mechanisms.

The Analysis of the Short-term Capital Movements by Using the VAR Model: The Case of Turkey

This paper investigates the relations among short-term capital inflows, government deficit, interest rate differentials, real exchange rate and some accounts of the balance of payments in Turkey in 1990s by using the vector autoregression (VAR) technique. The dynamic behaviours of each variable due to random shocks given to short-term foreign liabilities are captured by impulse response functions, and the portion of variance in the prediction for each variable in the system that is attributable to its own innovations and to shocks to other variables in the system is analysed by variance decomposition method. It is found that the policy of high interest-low exchange rate (hot money) is the main reason for the short-term capital inflows in Turkey, and we propose some main controls on capital inflows to limit some of the macroeconomic repercussions of these inflows.

Monetary Policy Schocks and Economic Growth in Nigeria

This study examines monetary policy shocks and economic growth in Nigeria. This study following ex post facto research design employed a regression model where economic growth was the dependent variable while money supply, inflation and interest rate were the explanatory variables. Time series data over the period of 1986 to 2018 sourced from Central Bank of Nigeria (CBN) Statistical Bulletin and World Bank Development Index (WDI) was utilized. The study employed the Vector Autoregression (VAR) techniques in the analysis. The result of the vector autoregression estimation shows that money supply exert a significant positive effect on economic growth in Nigeria while inflation and interest rate exert an insignificant positive effect on economic growth in Nigeria. The result proves that monetary policy shocks exert a significant effect on economic growth in Nigeria while interest rate and inflation do not show any effect. It was recommended that the CBN should ensure the downward review of the Monetary Policy Rate of 12% to 9 percent so as to enhance more financial accessibility.

Global Energy Price Volatility and Agricultural Commodity Prices in Malaysia.

Few studies have differentiated oil demand shocks from oil supply shocks in the literature that has investigated the impacts of these issues on the prices of agricultural products. This study attempts to investigate this problem by employing a structural vector autoregression (SVAR) technique on Malaysian data from January 1993 to December 2019. We found that the reactions of agricultural commodity prices to the changes in global oil prices largely depend on whether they result from oil demand shocks or oil supply shocks. Global oil demand shocks before the food price crisis (2006–2008) can explain a large share of the changes in prices of agricultural products, while after that period, their capacity to explain these changes becomes much weaker. After the food crisis period, the contribution of the oil supply shock to changes in the prices of agricultural products is higher than that of the oil demand shock. We can conclude that the role of oil supply in the economy in explaining changes in the prices of agricultural commodities is stronger after the food price crisis. This is because Malaysia’s economy, as a net oil exporter, benefits from higher oil prices resulting in higher demand for agricultural products and, consequently, higher prices for agricultural commodities.

A prediction on the impacts of China’s national emissions trading scheme on CO2 emissions from electricity generation

One of the government policies that can reduce CO2 emissions is the Emissions Trading Scheme (ETS), which was implemented in the Chinese economy on 16 July 2021. It is the largest ETS in the world, covering 12% of global CO2 emissions. Since this policy has not been experienced in China, it is necessary to predict its impact on CO2 emissions in this country. Furthermore, electricity and heat production is the major contributor to total CO2 emissions from fuel combustion. Therefore, this study attempts to predict the impact of the emissions trading scheme on CO2 emissions from the combustion of coal, oil and natural gas in electricity generation using annual data from 1985 to 2019. For this purpose, this study first predicts CO2 emissions from the combustion of coal, oil and natural gas for electricity generation in power plants using ARIMA and structural Vector Autoregression (SVAR) techniques over the 2020–2030 period. It then estimates the short- and long-run impact of the ETS policy on CO2 emissions from the combustion of coal, oil and natural gas in power plants over the projected period (2020–2030) by employing the ARDL methodology. The results suggest that the ETS policy is effective in reducing the CO2 emissions from the combustion of all fuels in electricity generation over the long-run. This is because of the increase in CO2 emissions from the combustion of these fuels in power plants in the long run, which exceed the threshold value. But in the short-run, it has a negative and statistically significant impact only on CO2 emissions from the natural gas power plants. These results suggest that improving the efficiency of all fuels can significantly reduce CO2 emissions in electricity generation from coal, oil and natural gas in the short- and long-run. They also enable China’s energy policymakers to update the ETS policy in its next phases.

The impact of external shocks on economic growth: An empirical study based on the SVAR models

Abstract The paper contains a series of complex analyses on the study of typologies of economic crises and can bring a significant contribution to the literature in determining the effects of external factors on economic growth, taking into account the distinct characteristics of the periods of decline. The work includes Hodrick-Prescott filtering techniques for characterizing business cycles in three Central and Eastern European countries and the Structural Vector Autoregression (SVAR) technique is used to analyze the impact of external shocks on economic growth over two distinct time-horizons. External shocks such as external debt, external interest rate, external output, producer price index and real interest rate were taken into account. For each economy analyzed, the impact of the two types of economic crisis was observed, namely financial crisis and health crisis, and two time-horizons were defined for each complete economic cycle. Over these two time-horizons, the impact of external shocks on economic growth has been assessed. There has been a general decrease in the effects of shocks in the second time-horizon, in which the most severe values of economic growth are associated with the health crisis, compared to the time-horizon associated with the financial crisis. It has also been observed that, in the case of both Hungary and Romania, the responses of economic growth to external shocks are faster compared to the Czech economy. Moreover, external production is the factor that explains most of the variance in the economic growth rate in the first time-horizon, while in the second, one of the most influential indicators is the external production price index, which has been severely affected by the slowdown in the global production process.

The Transmission Channel of Monetary Policy to the Real Economy Revisited: Evidence From Sierra Leone

This study examined the transmission channel of monetary policy to real economy in Sierra Leone using quarterly data from 2002 to 2018. The non-recursive structural vector autoregressive technique was employed to identify the channel of monetary policy transmission to the real economy. This technique was considered appropriate because it has two-way or bidirectional causal effects among endogenous variables and ordering of endogenous variables are considered flexible. Analysis of data shows that the exchange rate channel was found to be appropriate in transmitting monetary policy effect to real economy based on the results of impulse response and variance decomposition analysis. In light of the empirical findings, the study recommended that in a bid to have an effective monetary policy, the channels of monetary policy transmission, especially the exchange rate channel, should be taken into consideration in the design of monetary policy in Sierra Leone.

Monetary Policy Transmission Mechanism in Macroeconomic Activities in Pakistan (Wealth Channel)

This paper empirically analyzed the monetary policy transmission mechanism for wealth channels by applying Vector Auto Regressive (VAR) technique to time series data for the period of 1991 Q1 to 2018 Q4. Results are found significant. Variables included in the model follow the same direction as the theory suggests. Standard deviation shocks to each variable in variance decomposition results are bitterly transmitted. The performance of this channel on the biases of impulse responses and variance decomposition is better. Policy decisions related to high interest rates should be taken carefully. The level of savings is very poor. Low saving adversely affects investment and GDP. Therefore, better remedies are needed to capture the problem.

Investigating the performance of agricultural sector on well-being: New evidence from Burkina Faso

Burkina Faso’s economy is based mostly on agriculture. Despite this sector’s substantial contribution to economic development, the majority of the population continues to live below the poverty line, and poverty is even more pronounced in rural areas where subsistence farming is the main source of income. The present research intends to assess the effects of the agriculture sector on the wellbeing of society in Burkina Faso from 1970 to 2017 using a Vector Autoregressive technique. The results reveal that agriculture sector has an adverse influence on well-being in both short- and long-run when household consumption expenditure (HCE) used as a proxy of well-being. While this sector uncovered a productive impact on well-being measured by education (EDU) in both short- and long-run. An increase in the agriculture value-added induces an extend in the short-run and a reduction in the long-run of life expectancy (LEXP) in the Burkina Faso. The variance decomposition results show that the agricultural sector will contribute about 57.33% to explain variation in the household final consumption expenditure while industry and service sectors will only contribute about 2.03% and 4.42% respectively. However, the value-added from the industrial sector affects significantly (47.37%) the variation of life expectancy at birth in Burkina Faso. In addition, Granger’s causality test has demonstrated a unidirectional causal impact from agriculture value-added to household income. The same causal links were also discovered, respectively from the agricultural and service sectors to life expectancy. This study emphasizes the necessity to concentrate stakeholders including farmers, policymakers and experts on agri-business strategies and programs, investment in farm commodity processing in the growing country concerned. The farmers may thus change from subsistence to agri-business, therefore accelerating the industry’s growth and creating more jobs for the working population and diversifying the country's household income sources.

Sovereign risk spillovers: A network approach

Understanding the global financial network for sovereign debt, particularly with a focus on interaction and spillover effects of sovereign risk, has become important for policy makers as they look to protect the stability of their economies. Using high dimensional Vector Autoregression techniques and network simulation on Sovereign Credit Default Swaps (CDS)’ data of 57 countries, we identify that the global sovereign CDS network is fully integrated as there is virtually no country without any connection to at least one specific node in the system. However, each country has a unique attribute in the network, as a risk exporter or importer and/or risk transmitter. Among developed countries, the US (unsurprisingly) holds the dominant position as a risk exporter while Germany is identified as a connecting country that transmits shocks. The most connected countries in the sovereign CDS network belong to the new European Union members. We examine possible drivers of the network relationships observed, in order to better understand the risk transmission process, and find that connections in the sovereign risk network are stronger within regional groups and countries with the same level of economic development. Central and Eastern Europe and Middle East and Africa have more interactive networks than Northern Western Europe, Asia Pacific and Latin America. We also identify that financial volatility and economic policy uncertainty increase the interactions in market-based default risk assessment.

Forecasting of a complex phenomenon using stochastic data-based techniques under non-conventional schemes: The SARS-CoV-2 virus spread case

Epidemics are complex dynamical processes that are difficult to model. As revealed by the SARS-CoV-2 pandemic, the social behavior and policy decisions contribute to the rapidly changing behavior of the virus' spread during outbreaks and recessions. In practice, reliable forecasting estimations are needed, especially during early contagion stages when knowledge and data are insipient. When stochastic models are used to address the problem, it is necessary to consider new modeling strategies. Such strategies should aim to predict the different contagious phases and fast changes between recessions and outbreaks. At the same time, it is desirable to take advantage of existing modeling frameworks, knowledge and tools. In that line, we take Autoregressive models with exogenous variables (ARX) and Vector autoregressive (VAR) techniques as a basis. We then consider analogies with epidemic's differential equations to define the structure of the models. To predict recessions and outbreaks, the possibility of updating the model's parameters and stochastic structures is considered, providing non-stationarity properties and flexibility for accommodating the incoming data to the models. The Generalized-Random-Walk (GRW) and the State-Dependent-Parameter (SDP) techniques shape the parameters' variability. The stochastic structures are identified following the Akaike (AIC) criterion. The models use the daily rates of infected, death, and healed individuals, which are the most common and accurate data retrieved in the early stages. Additionally, different experiments aim to explore the individual and complementary role of these variables. The results show that although both the ARX-based and VAR-based techniques have good statistical accuracy for seven-day ahead predictions, some ARX models can anticipate outbreaks and recessions. We argue that short-time predictions for complex problems could be attained through stochastic models that mimic the fundamentals of dynamic equations, updating their parameters and structures according to incoming data.

The impact of banks' financial performance on environmental performance in Africa.

To better understand Africa's banks and the environment, this study investigates the impact of financial performance on environmental performance in Africa. We examined financial performance, environmental performance, and some control indicators dated from 2000 to 2016 by applying panel quantile regression and panel vector autoregressive techniques. Our results indicate that (i) in North African countries, carbon emission had a significant negative impact on financial performance on the 25th quantile and (ii) in the South, carbon emission had a statistically positive impact on financial performance on the 25th and 50th quantiles with the marginal effect increases from the lower quantile to the highest quantile. Also, bank deposits statistically negatively impacted financial performance on the 25th and 50th quantiles for both North and South economies. The dynamic panel quantile results show dissimilar effects at different quantiles. Also, the panel vector autoregressive results show that in North Africa carbon emission had a positive impact. Our results validate the stability test of the panel vector autoregressive model. The granger causality results in the North show a bilateral causal link between carbon emission and bank credit, carbon emission, and bank deposit. Since sustainability has become one of our era's most thorny issues, this paper provides extensive policy directives to assist African nations in boosting a greener future.

DYNAMIC MODELLING OF THE INFLUENCE OF DIASPORA CASH REMITTANCE ON MACROECONOMIC STABILITY IN NIGERIA

<p>Remittance flows into low-income and fragile states represent a lifeline that supports households as well as provides much-needed tax revenue (IMF - Sayeh & Ralp Chami; 2021).<strong> Purpose</strong>: on the basis of this record, the study sought to examine the dynamic modelling of the influence of diaspora cash remittance as measured by Personal Remittances Received (PRR); Exchange Rate (EXCHR); and Outward Remittances Flows (ORF) on macroeconomic stability in Nigeria as measured by Unemployment Rate (UNEMPR) and Gross Domestic Product per capita growth (GDPpcgr) using quarterly time-series data sourced from World Bank and World Development Indicators for the periods 2010Q1-2020Q4.<strong> Technique/Approach</strong>: the study was disintegrated to apply Engle-Granger two-step method of error correction model (ECM) together with Granger Causality test to analyse the causal effect of Personal Remittances Received; Exchange Rate; Outward Remittances Flows on Unemployment Rate, as well as, utilize vector autoregressive (VAR) technique to investigate the dynamic influence of Personal Remittances Received; Exchange Rate and Outward Remittances Flows on gross domestic product per capita growth.<strong> Findings</strong>: the result of Granger Causality test upheld the hypothesis of PRR does not involve Granger causality of UNEMPR and the hypothesis that UNEMPR does not involve Granger causality of PRR. However, unidirectional causality runs from EXCHR to UNEMPR; as well as, from ORF to UNEMPR. The result of the error correction model (ECM) demonstrated that personal remittances received and exchange rate have insignificant and significant short-term and long-term effects on increasing the rate of unemployment. Whereas, outward remittances flow significantly minimized the rate of unemployment. More so, the results of the vector autoregressive (VAR) technique portrayed that the past realization of GDPpcgr was associated with a significant increase of 0.84 percent in GDPpcgr. Whilst, the past realization of Personal Remittances Received and outward remittances flows were related to an insignificant increase in GDPpcgr respectively; also, the past realization of exchange rate retarded the GDPpcgr. Furthermore, variance decomposition forecast of 4-period horizon reported that 100 percent of deviation in GDPpcgr is explicated by GDPpcgr in the short-term, indicating that personal remittances received, exchange rate, and outward remittances flows had no strong exogenous influence on predicting GDPpcgr in the future. Whereas, in the long-term forecasted error in GDPpcgr produced about 97.57 percent; while, Personal Remittances Received, exchange rate and outward remittances flow had a weak influence on predicting GDPpcgr in the future.<strong> Concluding Remark</strong>: the study concluded that it is an imperative for policy makers to design more policy measures that will encourage, facilitate a smooth and efficient inflow of cash remittance from abroad into the country so as to stabilize the economy.</p><p> </p><p><strong>JEL: </strong>E01; E20; E24<strong></strong></p><p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0965/a.php" alt="Hit counter" /></p>

Quantifying the impacts of online fake news on the equity value of social media platforms – Evidence from Twitter

Online Fake News characterized by falsehood and ambiguity is significantly shaking up various aspects of social, economic, and political life across the globe. In addition, it can also be detrimental to the existence of social media platforms. In this research, by synthesizing the prior literature on negativity bias in online settings, reasons for platform failure and the characteristics of social media platforms, we explain the mechanisms through which online fake news impacts the equity value of these platforms. We also develop and implement a two-stage Bayesian Vector Autoregression technique to test these mechanisms using a dataset from Twitter. Our results show that falsehood results in an equity value loss of approximately 2.11 Million USD over a ten-day period while a mere 67.17 Million falsehood tweets can interact with ambiguity to produce a loss of 10 Million USD. We also find that ambiguity helps mitigate the negative impact of fake news which we attribute to the fact that users converse and disambiguate news that arrives on social media platforms. Our research has theoretical and practical implications for the impact of fake news on these platforms and their valuations.

Investigating the Relationships between Renewable Energy Consumption, Socio-Economic Factors and Health: A PVAR Analysis from MENA Net Oil Importing Countries

In this paper, we tried to contribute to the previous literature by analyzing the relationship between renewable energy consumption, socio-economic factors and health in the presence of a stringent environmental policy and lobbying power. Using a Panel Vector Auto-Regressive (PVAR) technique, we specifically examine the role of the government effectiveness and the lobbying pressure in moderating the impact of renewable energy consumption on CO2 emissions, economic growth and health factor considering the case of Middle East and North Africa (MENA) Net Oil Importing Countries (NOICs) from 1996 to 2019. Our analysis shows that (i) environmental policy stringency and good governance will induce a rise in the level of renewable energy consumption; (ii) lobbying power and interest groups discourage the renewable energy sector’s development since the add in economic growth of these economies is not oriented towards renewable energy projects; (iii) a rise in renewable energy consumption, perhaps generated by renewable energy policies, should favor the improvement of public health. Finally, the political implications of the findings are summarized and discussed.