Impulse Response Function Analysis Research Articles

Retracted] Evaluation Model and Decision Analysis of Digital Firms Ranked in Forbes’ Top Companies

This study evaluates the profitability and marketability efficiencies of digital firms ranked in Forbes’ list of top companies by using a two‐stage network data envelopment analysis (DEA) model with multiplicative efficiency aggregation under the second‐order cone programming (SOCP) and examines the respective impacts of the 1995–2001 dot‐com bubble and the 2007–2009 global financial crisis on the companies’ efficiencies by applying impulse response function (IRF) analysis. The data of our 49 sampled companies are derived from the Compustat database. The covered period is 1999–2018. These results present the stable and increasing improvement of profitability and marketability efficiencies; in addition, two crisis events have no significant impact on the performance of digital firms. This research is supposed to offer a reasonable and objective evaluation model to measure the performance of digital firms, providing the managers and investors a reference for making their decision.

Оценка влияния глобальных шоков на российскую экономику в рамках факторной модели

In this study, we estimate the contribution of global demand, supply and commodity shocks to the dynamics of Russian macroeconomic variables. The main tool used in this work is a factor augmented vector autoregression (FAVAR) that allows extracting global factors from a wide range of variables. Recursive and sign restrictions are used to identify global shocks. Russian economy is represented by a large set of informational series aggregated into a small number of factors. FAVAR approach allows for extended inference on the reaction of Russian macroeconomic variables to global shocks. Impulse response function analysis shows that Russian economy is affected by all three specifi ed global shocks and forecast error decompositions indicate that those shocks account for nearly 80 per cent of key variables dynamics. We also showed that global demand and global commodity shocks were more crucial compared to the third type of shocks in explaining macroeconomic dynamics.

Bootstrapped nonlinear impulse-response analysis: the FTSE100 (UK) and the NDX100 (US) indices 2012-2021

This paper presents bootstrapped nonlinear impulse response function analyses for general step ahead mean and volatility densities. From strictly (ergodic and) stationary series and BIC optimal nonlinear model coefficients, the paper establishes step-ahead densities for both the conditional mean and volatility. For sampling variances using one thousand samples and conditioning all paths on the daily impulses -5, -3, ..., 5% all mean and volatility responses show mean reversion. For the volatility, all increases seem to arise from negative index movements suggesting strong asymmetry. Furthermore, the model coefficients for the volatility exhibit data dependence suggesting ability to predict volatility. The indices report some striking step-ahead differences for both the mean and the volatility. For the mean, only the NDX100 seems to show overreactions. For the volatility, for both positive and negative impulses the NDX100 reports higher volatility responses then FTSE100. However, asymmetry manifested for both indices suggesting that trading volatility as an asset may insure against market crashes and be an excellent diversification instrument. Finally, using a stochastic volatility model to obtain calibrated functions that give step-ahead predicted values for static predictions, enriches participants' derivative trading strategies (i.e., volatility swaps).

Economic Freedom and the Determinants of the Bank Spread in South America

This paper performs panel data analysis to test the existence of an inverse relationship between bank spreads and the degree of economic freedom in South American countries between 2000 and 2020. In the late 1990s, South America began a process of financial sector reforms, which included in almost all countries the liberalization of interest rates (instead of capping) and the elimination of direct credit allocation mechanisms. By hypothesis, it is expected that the greater the economic freedom, the lower the degree of financial regulation. This would reduce the transaction costs of financial institutions and contribute to reducing the banking spread (assuming constant credit risk). The traditional methodology is applied here, complemented by unit root and cointegration tests, in addition to impulse-response function analysis, in the context of panel autoregressive vectors (VAR). The results show that economic freedom and monetary credibility (component area of the EFW, Economic Freedom of the World index) negatively affect the value of the spread, with long-run effects as well.

FACTORS THAT INFLUENCE MONEY / M2 MONEY IN INDONESIA (DATA PERIOD Q1.2001 - Q4.2015)

This study aims to analyze the demand for money (broad money / M2) with a model that uses the condition of non-stationary data so that it can estimate the need for money in the economy. The period of data studied is from Q1.2001-Q4.2015. The analysis technique used is the Vector Error Correction Model (VECM) by conducting data stationarity tests, cointegration tests, lag feasibility tests, VECM Estimates, Granger Causality Test, and Impulse Response Function analysis to determine the effect ofshock from other variables.
 The results of this study indicate that: 1) GDP has a positive influence both in the short and long term on the money supply (M2); 2) Exchange rates or exchange rates also have a positive influence on M2; 3) Interest rates negatively affect M2;4) Inflation has a positive effect on M2.
 
 Keywords: Money supply (M2), GDP, exchange rate / exchange rate, interest rates and inflation

Analysis of the Propagation Effects of Remittances on the Vulnerability of External Trade of the Republic of Moldova

In the Republic of Moldova remittances have become a much-discussed subject, the country ranking among the economies with the highest share of remittances in terms of GDP. What is more, remittances, unlike FDI, external trade and other sources of income, seem to have a significant impact on economic growth. Republic of Moldova is a small open economy vulnerable to external shocks. We will examine the effect of remittances on the balance of trade by creating an econometric model. Am attempt has also been made to capture the positive and negative spillovers that migrants’ remittances have on a country’s socio-economic development. Within the research a variety of analytical tools are employed including Granger causality tests, unit root tests, coupled with a structural vector auto regression (SVAR), impulse response function (IRF) analyses and variance decomposition. We find that net trade and remittances are closely associated and follow an almost identical path. Remittances have strong effect on the growth of negative net trade of the Republic of Moldova.

Contribution of conventional bank lending for agricultural sector in Indonesia

This study examines the determinant contribution of conventional bank lending for the agricultural sector in Indonesia. The analysis method used in this research is the Vector Correction Model (VECM). The results showed that in the short term, there was no significant effect of the Non-Performing Loan (LogNPL), GDP of Agricultural Sector (LogPDB), and Agricultural Sector Credit Interest Rates (SBK). However, there is an effect of the LogNPL and LogPDB on the conventional bank lending for the agricultural sector in the long term. The LogNPL has a significant positive effect on the contribution of conventional bank lending to the agricultural sector. While the LogPDB has a significant negative effect on the contribution of conventional bank lending for the agricultural sector. The Impulse Response Function (IRF) analysis results show that shocks to the LogNPL respond negatively in the long run, shocks to the LogPDB respond positively in the long run, and shocks to the SBK respond negatively in the long run by conventional bank lending for the agricultural sector. Through the analysis of FEVD (Forecast Error Variance Decomposition), it is known that the biggest contribution to conventional bank lending for the agricultural sector is agricultural credit and GDP.

Energy and Bank Equity Interactions

Oil price shocks harm real output and bank and industrial profit in most oil-importing countries, which has motivated us to investigate the impact of these shocks on the equity performance of banking industries. To fulfill the research objectives, we involve a sample of developed and emerging economies for comparison purposes. The objective of employing the Toda and Yamamoto (Journal of econometrics, 1995, 66 (1), 225–250) causality test is to explore the time-variant relationship between oil prices and banking indices to investigate how oil price shocks affect the performance of country-specific banking industries. In addition, an impulse response function and variance decomposition analysis are utilized to, respectively, examine the time-variant relationship between oil price shocks and macroeconomic factors and the performance of the banking sector. Results vary across different economies in our sample, but the magnitude of oil price impact is relatively significant in the US, the UK, Canada, Japan, Mexico, and Brazil. The findings indicate that oil price rises adversely affect equity bank indices in developed and emerging economics except for Mexico. Notably, our findings show that oil prices and interest rates jointly have significant power in explaining the banking equity variation and suggest that international bank portfolio investors should consider hedging oil price risk.

Signal processing for architectural acousticians

Architectural acoustics is characterized by its multidisciplinary nature, the multiple disciplines include physical acoustics, engineering acoustics, noise control, psychoacoustics, and signal processing. In recent decades, signal processing has become an integrated body of fundamental knowledge of architectural acoustics. Furthermore, it has advanced technology in architectural acoustics practice. This talk highlights a number of applications in architectural acoustics in which acoustic signals need to be efficiently manipulated and analyzed. In addition, signal processing tools have drastically advanced measurement techniques in architectural acoustics, advanced spatial and temporal analysis of sound fields in enclosures. Signal processing has entered into a wide range of areas, from room-acoustic energy decay analysis, modal analysis, interaural de-correlation for quantifying auditory spaciousness, array signal processing, three-dimensional rendering techniques for auditory displays, time-frequency analysis of impulse response functions, to optimizations, machine-learning and the concept of Pareto Fronts in architectural acoustics. Architectural Acousticians who are equipped with and understand the basic tools of signal processing are able to contribute to advancing knowledge and perform best practices in the architectural acoustics.

Testing cointegration between workers' remittances and human capital formation in Sri Lanka

PurposeThis study investigates the long-run relationship between workers' remittances and human capital formation in Sri Lanka by using the macro-level time series data during the period of 1975–2020.Design/methodology/approachIn this study, the augmented Dickey–Fuller (ADF) and Philips–Perron (PP) unit root tests, the autoregressive distributed lag (ARDL) bounds cointegration technique, the Granger causality test, the forecast error variance decomposition technique and impulse response function analysis were employed as the analytical techniques.FindingsIn accordance with the results of unit root tests, the variables used in this study are mixed order. Results of cointegration confirm that workers' remittances in Sri Lanka have both long-run and short-run beneficial relationship with human capital formation. The Granger causality test results indicate that there is a two-way causal relationship between workers' remittances and human capital formation. The results of forecast error variance decomposition expose that innovation of workers' remittances contributes to the forecast error variance in human capital in bell shape. Further, the empirical evidence of impulse response function analysis reveals that a positive standard deviation shock to workers' remittances has an immediate significant positive impact on human capital formation in Sri Lanka for a period of up to ten years.Practical implicationsThis research provides insights into the workers' remittances in human capital formation in Sri Lanka. The findings of this study provides evidence that workers' remittances help to produce human capital formation.Originality/valueBy using the ARDL Bounds cointegration and other techniques in Sri Lanka, this study fills an important gap in academic literature.

Reinvestment of earnings in Polish FDI inflows

Abstract The aim of this paper is to diagnose the cause-and-effect relationships between reinvestment of earnings (RoE) and other components of FDI inflows and GDP in Poland in the years of 2004–2019, using the VECM model**. Changes in the structure of FDI inflows in Poland are in line with the stages of the FDI life cycle. The increase in the share of RoE in the structure of these investments is also accompanied by an increase in the impact and the degree of explanation of changes in GDP. Studies confirmed that changes in the structure of FDI in Poland was adequate to the theoretical cycle of FDI life. The increase in the share of RoE in the structure of FDI inflows is accompanied by a decrease in equities. The VECM model, impulse response function and decomposition analysis confirmed that among FDI components mainly equities, and next, RoE have large participation in the degree of explanation of GDP. In the short-term, mainly equity has the most important impact on GDP, and additionally, RoE. In the long-time, the importance of equity decreases, while increases the impact of RoE, and also, debt instruments. The increase in the share of RoE in the structure of FDI inflows accompanied by the increase in the impact of these investments on GDP changes.

COVID-19-induced shocks and uncertainty

Using statistical identification, we extract a COVID-19-induced shock by exploiting large daily jumps in financial markets caused by news about the pandemic. This shock depresses economic and financial indicators, increases risk and uncertainty measures, has sizeable distributional effects, and hits most harshly those industries relying on face-to-face interactions. Impulse response function analysis across various identification strategies leads us to interpret the statistical COVID-19-induced shock as a structural uncertainty shock.

The Impact of COVID-19 on Individual Industry Sectors: Evidence from Vietnam Stock Exchange

The paper examines the impact of the COVID-19 pandemic on the stock market prices. The vector autoregression model (VAR) has been used in this analysis to survey 341 stocks on the Ho Chi Minh City Stock Exchange (HOSE) for the period from January 23, 2020 to December 31, 2020. The empirical results obtained from the analysis of 11 economic sectors suggest that there is a statistically significant impact relationship between COVID-19 and the healthcare and utility industries. Additional findings show a statistically significant negative impact of COVID-19 on the utility share price at lag 1. Analysis of impulse response function (FRF) and forecast error variance decomposition (FEVD) show an inverse reaction of utility stock prices to the impact of COVID-19 and a gradual disappearing shock after two steps. Major findings show that there is a clear negative effect of the COVID-19 pandemic on share prices, and the daily increase in the number of confirmed cases, indicate that, in future disease outbreaks, early containment measures and positive responses are necessary conditions for governments and nations to protect stock markets from excessive depreciation. Utility stocks are among the most severely impacted shares on financial exchanges during a pandemic due to the high risk of immediate or irreversible closure of manufacturing lines and poor demand for basic amenities.

An impulse response function analysis of the impact of modern payment technologies on money demand in Nigeria

An impulse response function analysis of the impact of modern payment technologies on money demand in Nigeria

Economic Factors Affecting Rice Price Fluctuation in North Sumatera

The research approach method is a qualitative approach. The method of data collection is secondary data, secondary data needed is obtained from relevant agencies, namely from the Central Bureau of Statistics and the Department of Agriculture as well as other literature related to research. The analytical method used is descriptive analysis and analysis of Vector Auto Regression (VAR). The results showed that: 1) The dominant factors affecting rice prices in North Sumatra are 2, the first is 60% production because the higher the production of rice, the price of rice will decline and the lower the production, the price of rice will increase and the second factor is 38% inflation because if the price of rice continues to increase there will be inflation, but it is different from the fact that rice prices fluctuate due to the stability of rice prices. 2) Factors that affect rice prices in North Sumatra in the short term are significant, namely inflation and in the long term there are five significant factors, namely production (prod), harvest area (field), income (inc), consumption (cons) ) and inflation (inf). 3) From Impulse Response Function Analysis, it can be seen that the factors that influence rice prices in North Sumatra can be seen as stability, namely the production variable (Prod) reaches stability in the 25th period, the penen variable (Field) reaches stability in the period 28, the consumption variable (Cons) reaches stability in the 25th period, the income (Inc) variable reaches stability in the 20th period, the inflation variable reaches stability in the 27th period. namely inflation and in the long term there are five significant factors, namely production (prod), harvest area (field), income (inc), consumption (cons) and inflation (inf).

A Study on Total Energy Production, GDP, Total Investment in Fixed Capital and Population in Shandong Province

This paper is to aim at analysing the responses of total energy production from the impulses of GDP, total investment in fixed assets and population in Shandong. The impulse response function analysis indicates that Shandong energy production will be greatly influenced by the GDP impulses in the short run and the influences from total investment in fixed capital assets is the smallest in the short run. The influence of total energy production by the population is rather medium compared with the GDP and investment in fixed capital assets. So we can see that GDP growth will greatly influence total energy production. It is necessary for administration to pay attention to the GDP growth as concerning the planning of total energy production.

PENGARUH JUMLAH UANG BEREDAR DAN TINGKAT SUKU BUNGA TERHADAP KURS RUPIAH MENGGUNAKAN VECTOR ERROR CORRECTION MODEL

This study aims to determine the influence on the estimated short-term and long-term relationships of the VECM (Vector Error Corrction Model), the casuality relationship of the three variables, and the length of response effect time when achieving stability. The data used is monthly data for the period 2007 - 2017. The estimated result obtained by the model is VECM at lag 2 with the results of the short-term estimate KURSt = - 0.257 KURSt-1 - 0.289 KURSt-2 - 0.029 TSBt-1, JUBt = 0.015 - 0.369 KURSt-2 - 0.208 JUBt-1- 0.202 JUBt-2, TSBt = 0.275 TSBt-1 + 0.353 TSBt-2 where t time period and long-term estimated results that the amount of money in circulation and the interest rate negatively affect the rupiah exchange rate. In granger casuality test, there is only a direct relationship between the rupiah exchange rate and the amount of money in circulation and the interest rate with the rupiah exchange rate. Based on the analysis of impulse response function, when given the shock of interest rate and rupiah exchange rate itself, the effect of rupiah exchange rate response is stable in the 22nd period and the 15th period, when given the shock of rupiah exchange rate and the amount of money in circulation itself, the effect of the response of the amount of money in circulation is stable in the 10th period and when given the shock of the interest rate itself, the effect of the response of the interest rate is stable in the 18th period.Keywords: impulse response function. interest rate, money supply, rupiah exchange rate, VECM model

Estimating effects of ICT intensity on productivity, employment and output in South Africa: an industry-level analysis

ABSTRACT This article aims to estimate the effects of ICT intensity on labor productivity, employment and output of agro-processing industries. To achieve this, the ICT intensity index is applied to rank industries into ‘more ICT-intensive’ and ‘less ICT-intensive’ groups. Thereafter, the annual growth rates of labor productivity, employment and output were calculated. Ultimately, the effects of ICT intensity were examined using Pooled Mean Group estimation, the Toda and Yamamoto Granger Non-Causality Test, and the Impulse Response Function and Variance Decomposition analyses. The findings suggest that ICT intensity yields higher positive and significant effects on the growth of the more ICT-intensive industries. Evidence of a causal relationship was detected for the more ICT-intensive industries. The findings further proved that ICT intensity contributed more to the forecast error variance in the growth of the more ICT-intensive industries. Overall, this article provides evidence of ICT-led growth for industries that use ICT most intensively.

Assessing the Dynamic Relationship Between Macroeconomic Factors and Stock Market Movement: Evidence from China

This paper examines short-run and long-run dynamic relationships between selected macroeconomic variables and stock prices in the China Stock Exchange proxy by Shanghai Composite Index. The data is restricted to the period for which quarterly data are available from 1992 Q1 to 2019 Q4 (112 observations) retrieved from the Federal Reserve Bank of Saint Louis, GTA-CSMAR database, and CEIC Database. The study employs unit root test, cointegration test, vector error correction estimates, and Innovation Accounting (impulse response test). A Johansen-Juselius cointegration test indicates a positive long run relationship between the Chinese stock price index and exchange rate, and a negative long run relationship with the gross domestic product, and M2 money supply. An estimated vector error correction model (VECM) suggests significant unidirectional short run causal relationships between Chinese stock market returns and money supply but not for inflation. The VECM also finds a significant long run causal relationship among the macroeconomic variables in the system. The estimated speed of adjustment indicates that the Chinese stock market converges to the equilibrium within half a year. Impulse response function analysis shows no significant relationship between China stock market returns and the macroeconomic variables. Forecast error variance decompositions suggest that 76% of the variation in Chinese stock market returns is attributable to its own shock, which implies that Chinese stock market returns are relatively independent of the macroeconomic variables in the system. Keywords: Stock Prices, Macroeconomic Variables, Cointegration, Innovation Accounting, China. JEL Classification : G15, E44, C58, O53 DOI: 10.7176/RJFA/12-6-02 Publication date: March 31 st 2021

Sensitivity estimation of first excursion probabilities of linear structures subject to stochastic Gaussian loading

This contribution focuses on evaluating the sensitivity associated with first excursion probabilities of linear structural systems subject to stochastic Gaussian loading. The sensitivity measure considered is the partial derivative of the probability with respect to parameters that affect the structural response, such as dimensions of structural elements. The actual calculation of the sensitivity demands solving high dimensional integrals over hypersurfaces, which can be challenging from a numerical viewpoint. Hence, sensitivity evaluation is cast within the context of a reliability analysis that is conducted with Directional Importance Sampling. In this way, the sought sensitivity is obtained as a byproduct of the calculation of the failure probability, where the post-processing step demands performing a sensitivity analysis of the unit impulse response functions of the structure. Thus, the sensitivity is calculated using sampling by means of an estimator, whose precision can be quantified in terms of its standard deviation. Numerical examples involving both small- and large-scale structural models illustrate the procedure for probability sensitivity estimation.