scholarly journals SVAR ANALYSIS OF THE IMPACTS OF CORPORATE TAXATION ON THE MACRO ECONOMY OF LITHUANIA

Ekonomika ◽  
2012 ◽  
Vol 91 (4) ◽  
Author(s):  
V ioleta Klyvienė ◽  
Jaunius Karmelavičius
Keyword(s):  
Fiscal Policy ◽  
Corporate Taxation ◽  
Empirical Literature ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Structural Vector Autoregression ◽  
Svar Model ◽  
Capital Tax ◽  
The Impact ◽  
Structural Vector

Abstract. This study aims to investigate the effects of tax policy on the macroeconomic variables of Lithuania. Special attention is devoted to conclusions concerning the impact of corporate taxation. The methodological framework is structural vector autoregression models identified using the Cholesky and Blanchard–Perotti approaches. Investigations of the impact of fiscal policy have been scarce in the empirical literature of Lithuania. The authors of this article use the methodology of assessing the impacts of fiscal policy that has not been used in Lithuania so for.JEL classification: E62, H25, F21.Key words: SVAR model, impulse response functions, fiscal policy, capital tax, investment

THE REGIONAL ASYMMETRIC RESPONSES TO CENTRAL BANK’S MONETARY POLICY IN PAKISTAN

2017 ◽  
Vol 65 (02) ◽  
pp. 351-364
Author(s):  
NASEEM FARAZ ◽  
ZAINAB IFTIKHAR
Keyword(s):  
Monetary Policy ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Structural Vector Autoregression ◽  
Monetary Policy Shocks ◽  
Limited Evidence ◽  
Svar Model ◽  
Policy Shocks ◽  
National Output ◽  
Structural Vector

Literature on differential impacts of monetary policy across regions discusses several factors which may be responsible for asymmetrical effects of monetary policy. As far as Pakistan is concerned, limited evidence is available for both mechanism and impact of monetary policy. In this study, we examine asymmetries in responses of real output of provinces to central bank’s monetary policy in Pakistan. We also attempt to explore the potential sources of these asymmetries. The Structural Vector Autoregression (SVAR) model is employed to examine each province’s response to unanticipated monetary policy shocks. The generalized impulse response functions from SVAR reveal that monetary policy has varied effects across the provinces. In two regions — Punjab and Sindh — monetary policy shocks cause variations in provincial outputs in similar ways. These responses are also comparable to the response of national output to changes in monetary policy but with considerable differences in magnitudes. While other provinces Khyber Pakhtunkhawa (KPK) and Balochistan show less sensitivity to unanticipated change in monetary policy. The less sensitive regions exhibit dissimilar responses both in timings and magnitudes. These dissimilarities in regional responses draw attention to devise an effective national monetary policy that might consider the cross-provincial differences in responses to central monetary policy in Pakistan.

scholarly journals How Does Fiscal Policy Affect Bank Credit? Evidence from China

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Huan Yan ◽  
Weiguo Xiao ◽  
Qi Deng ◽  
Sisi Xiong
Keyword(s):  
Fiscal Policy ◽  
Government Spending ◽  
Bank Credit ◽  
Tax Revenue ◽  
External Financing ◽  
Structural Vector Autoregression ◽  
Economic Data ◽  
Svar Model ◽  
Collateral Channel ◽  
Structural Vector

Using a set of Chinese economic data and a structural vector autoregression (SVAR) model, this paper investigates the transmission channels of fiscal policy to bank credit in China. We find that increases in tax revenue can increase bank credit through external financing premium channel, collateral channel, and bank liquidity channel. We also find that increases in government spending can reduce bank credit through bank liquidity channel and increase bank credit through external financing premium channel and collateral channel.

The Impact of Policy Uncertainty on Macro Variables – An SVAR-Based Empirical Analysis for EU Countries

2017 ◽  
Vol 68 (2) ◽  
Author(s):  
Dominik Kronen ◽  
Ansgar Belke
Keyword(s):  
Stock Market ◽  
Policy Uncertainty ◽  
Stock Market Volatility ◽  
Market Uncertainty ◽  
Vector Autoregressive ◽  
Svar Model ◽  
Negative Effect ◽  
Macro Variables ◽  
The Impact ◽  
Structural Vector

AbstractIn light of the rising political and economic uncertainty in Europe, we aim to provide a basic understanding of the impact of policy and stock market uncertainty on a set of macroeconomic variables such as production and investment. In this paper, we apply a structural vector autoregressive (SVAR) model to gain first insights that may help to identify avenues for further research. We find that stock market volatility shows a fairly consistently negative effect. However, the implications of policy uncertainty for Europe and the euro area in particular are not so straightforward.

Assessing the Macroeconomic Effects of Quantitative Easing: Empirical Evidence from the Federal Reserve’s Experience

2019 ◽  
Vol 67 (3-4) ◽  
pp. 233-245
Author(s):  
Achille Dargaud Fofack ◽  
Ahmet Aker ◽  
Husam Rjoub ◽  
Amin Sokhanvar
Keyword(s):  
Stock Prices ◽  
Economic Activity ◽  
The United States ◽  
Quantitative Easing ◽  
Structural Vector Autoregression ◽  
Monthly Data ◽  
Svar Model ◽  
The Us ◽  
Us Dollar ◽  
Structural Vector

This article aims at assessing the effects of the Federal Reserve’s quantitative easing (QE) programmes on both economic activity and prices in the United States. Using a structural vector autoregression (SVAR) model on monthly data from January 2007 to March 2017, it is assumed that a substantial fraction of the liquidity injected under the Federal Reserve’s quantitative easing programmes was used to artificially inflate stock prices. Furthermore, QE is assumed to be a competitive devaluation programme. The findings reveal that QE helps support economic activity, while its effect on inflation is rather small and insignificant. Besides, it is also found that QE boosts stock prices but does not have a significant effect on the US dollar.

The impact of media campaigns on smoking cessation activity: a structural vector autoregression analysis

Addiction ◽  
2012 ◽  
Vol 107 (11) ◽  
pp. 2043-2050 ◽  
Author(s):  
Tessa E. Langley ◽  
Ann McNeill ◽  
Sarah Lewis ◽  
Lisa Szatkowski ◽  
Casey Quinn
Keyword(s):  
Smoking Cessation ◽  
Vector Autoregression ◽  
Structural Vector Autoregression ◽  
Media Campaigns ◽  
The Impact ◽  
Structural Vector

scholarly journals Variation in emission metrics due to variation in CO<sub>2</sub> and temperature impulse response functions

2013 ◽  
Vol 4 (2) ◽  
pp. 267-286 ◽  
Author(s):  
D. J. L. Olivié ◽  
G. P. Peters
Keyword(s):  
Temperature Change ◽  
Impulse Response ◽  
Effective Means ◽  
Global Temperature ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Climate Effect ◽  
Time Horizons ◽  
Global Temperature Change ◽  
The Impact

Abstract. Emission metrics are used to compare the climate effect of the emission of different species, such as carbon dioxide (CO2) and methane (CH4). The most common metrics use linear impulse response functions (IRFs) derived from a single more complex model. There is currently little understanding on how IRFs vary across models, and how the model variation propagates into the metric values. In this study, we first derive CO2 and temperature IRFs for a large number of complex models participating in different intercomparison exercises, synthesizing the results in distributions representing the variety in behaviour. The derived IRF distributions differ considerably, which is partially related to differences among the underlying models, and partially to the specificity of the scenarios used (experimental setup). In a second part of the study, we investigate how differences among the IRFs impact the estimates of global warming potential (GWP), global temperature change potential (GTP) and integrated global temperature change potential (iGTP) for time horizons between 20 and 500 yr. Within each derived CO2 IRF distribution, underlying model differences give similar spreads on the metrics in the range of −20 to +40% (5–95% spread), and these spreads are similar among the three metrics. GTP and iGTP metrics are also impacted by variation in the temperature IRF. For GTP, this impact depends strongly on the lifetime of the species and the time horizon. The GTP of black carbon shows spreads of up to −60 to +80% for time horizons to 100 yr, and even larger spreads for longer time horizons. For CH4 the impact from variation in the temperature IRF is still large, but it becomes smaller for longer-lived species. The impact from variation in the temperature IRF on iGTP is small and falls within a range of ±10% for all species and time horizons considered here. We have used the available data to estimate the IRFs, but we suggest the use of tailored intercomparison projects specific for IRFs in emission metrics. Intercomparison projects are an effective means to derive an IRF and its model spread for use in metrics, but more detailed analysis is required to explore a wider range of uncertainties. Further work can reveal which parameters in each IRF lead to the largest uncertainties, and this information may be used to reduce the uncertainty in metric values.

scholarly journals The Impact of the PSR Rural Insurance Program on the Agricultural Productivity in the Matopiba Region of Brazil

2021 ◽  
Vol 12 (4) ◽  
pp. 1
Author(s):  
Francisco José da Silva Tabosa ◽  
Pablo Urano de Carvalho Castelar ◽  
José Eustáquio Ribeiro Vieira Filho ◽  
Domingos Isaías Maia Amorim ◽  
Maria Josiell Nascimento Da Silva
Keyword(s):  
Government Subsidy ◽  
Impulse Response Functions ◽  
Response Functions ◽  
Short Term ◽  
Insurance Program ◽  
Auto Regressive ◽  
Subsidy Program ◽  
Second Year ◽  
Soy Production ◽  
The Impact

The present work aims to analyze the impact of a government subsidy program of rural insurance in Brazil, (called the Programa de Subvenção ao Prêmio de Seguro Rural - PSR), on the productivity of insured producers in the MATOPIBA region of the country, which encompasses four Brazilian states, Maranhão, Tocantins, Piauí and Bahia, between the years 2008 to 2019. For this, municipalities were selected that had at least one insured producer throughout the analyzed period. The variables used were the number of producers, the number of insurance policies, the planted area, the productivity obtained and the insured financial amount of the producers. The methodological procedure was based on Auto-regressive Vectors (VAR) for panel data. The results showed a concentration, of all the variables used in the research, in the state of Bahia, mainly in the municipalities of Formosa do Rio Preto and São Desidério, whose main economic activity is soy production. It was also found that the impulse response functions on productivity obtained through a shock in the other variables, except the planted area variable, the others showed positive initial (short-term) responses until the second year. The average time for responses to smooth over time occurs from the sixth year onwards.

scholarly journals Oil Price Shocks, Systematic Monetary Policy and Economic Activity

2019 ◽  
Vol 58 (1) ◽  
pp. 65-81 ◽  
Author(s):  
Muhammad Zeshan ◽  
Wasim Shahid Malik ◽  
Muhammad Nasir
Keyword(s):  
Monetary Policy ◽  
Jel Classification ◽  
Oil Price ◽  
Oil Price Shocks ◽  
Structural Vector Autoregression ◽  
Price Shocks ◽  
Output Loss ◽  
The Impact ◽  
Auto Regression ◽  
Structural Vector

This study quantifies the impact of oil price shocks and the subsequent monetary policy response on output for Pakistan. It employs a quarterly Structural Vector Auto-regression framework for the period 1993–2015. It first discovers that Hamilton’s (1996) Net Oil Price Increase indicator appropriately reveals most of the oil price shocks hitting Pakistan’s economy. We find that a contractionary monetary policy, resulting from the oil price shocks, contributes to significant output loss in Pakistan. After encountering the Lucas critique, the present study finds that around 42 percent of the output loss is due to the ensuing tight monetary policy. This suggests that the central bank of Pakistan can reduce the impact of oil price shocks by reducing its intervention in the market. JEL Classification: E1, E3, E5 Keywords: Oil Price Shocks, Monetary Policy, Structural Vector Autoregression

scholarly journals The Shape of Eurozone’s Uncertainty: Its Impact and Predictive Value on GDP

2020 ◽  
Vol 7 (6) ◽  
pp. 1
Author(s):  
Ralf Fendel ◽  
Nicola Mai ◽  
Oliver Mohr
Keyword(s):  
Standard Deviation ◽  
Business Cycle ◽  
Financial Markets ◽  
Impulse Response ◽  
Two Dimensions ◽  
Point Estimate ◽  
Impulse Response Functions ◽  
Response Functions ◽  
The Business Cycle ◽  
The Impact

This paper examines the role of uncertainty in the context of the business cycle in the euro area. To gain a more granular perspective on uncertainty, the paper decomposes uncertainty along two dimensions: First, we construct the four different moments of uncertainty, including the point estimate, the standard deviation, the skewness and the kurtosis. The second dimension of uncertainty spans along three distinct groups of economic agents, including consumers, corporates and financial markets. Based on this taxonomy, we construct uncertainty indices and assess the impact on real GDP via impulse response functions and further investigate their informational value in rolling out-of-sample GDP forecasts. The analysis lends evidence to the hypothesis that higher uncertainty expressed through the point estimate, a larger standard deviation among confidence estimates, positive skewness and a higher kurtosis are all negatively correlated with the business cycle. The impulse response functions reveal that in particular the first and the second moment of uncertainty cause a permanent effect on GDP with an initial decline and a subsequent overshoot. We find uncertainty in the corporate sector to be the main driver behind this observation, followed by financial markets’ uncertainty whose initial effect on GDP is comparable but receding much faster. While the first two moments of uncertainty improve GDP forecasts significantly, both the skewness and the kurtosis do not augment the forecast quality any further.

EMPIRICAL STUDIES ANALYZING THE DYNAMIC EFFECTS OF CHANGES IN PUBLIC EXPENDITURE AND TAXATION ON ACTIVITY

2018 ◽  
Vol 28 (5) ◽  
pp. 1641-1646
Author(s):  
Mahije Mustafi ◽  
Sulbije Memeti Karemani
Keyword(s):  
Economic Growth ◽  
Fiscal Policy ◽  
Economic Activity ◽  
Empirical Studies ◽  
Empirical Literature ◽  
Budget Deficits ◽  
Dynamic Effects ◽  
Macroeconomic Impact ◽  
The Business Cycle ◽  
The Impact

This paper analyzes the empirical literature that examines the effects of fiscal policy shocks on economic activity. Discussion related to fiscal policy is related to the impacts on economic growth is quite current, because the development of appropriate fiscal instruments can lead to steady and sustainable economic growth in the countries. The role of fiscal policy and the impact on economic activity are among the most controversial issues among academics and policymakers. In the absence of any "active" intervention in government expenses, tax revenues move automatically with the economic cycle. I can also say that government transfers can be considered as help for the unemployed, they grow as the economy slows down and unemployment rises, while labor tax returns, capital and consumption flows are declining. Resistive actions occur when the business cycle improves. In recent years, empirical studies have shown that private consumption and GDP have increased significantly, while government expenses have been severely reduced. Most empirical evidence suggests that fiscal expansion increases production and consumption and worsens the trade balance.The Kenzie and Neoclassical schools have different views on the impact of public spending on economic activity. This study has completed a detailed review of many important, relevant scientific havepapersthat empirically document these impacts. As a conclusion, we can state that although the fiscal policy theory is well developed, until recently has not received much attention from the (applied) economic practice. The first category is aimed at assessing macroeconomic impact from major reductions in the budget deficit, and the second study, in general, analyzes the stabilizing capabilities of fiscal policy variables. According to Blanchard and Perotti, the dynamic effects of the discretionary fiscal policy of macroeconomic variables have recently focused on the omissions of autoregressive vectors (2002). Some empirical studies have found a link between budget deficits, money growth and inflation, both in industrialized economies as well as in growing economies. For industrial economies most of these studies have come to the conclusion that there is little evidence that government debt affects the growth of money and inflation. In developing countries, it is often argued that high inflation is realized when governments face large and ongoing deficits financed by money emission. A change in taxes or public expenses (the so-called “fiscal shocks”) at any time prevents their development.

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