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Journal articles on the topic 'Variance inflation model'

Author: Grafiati
Published: 4 June 2021
Last updated: 15 February 2022

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1

El Gharamti, Mohamad. "Enhanced Adaptive Inflation Algorithm for Ensemble Filters." Monthly Weather Review 146, no. 2 (2018): 623–40. http://dx.doi.org/10.1175/mwr-d-17-0187.1.

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Spatially and temporally varying adaptive inflation algorithms have been developed to combat the loss of variance during the forecast due to various model and sampling errors. The adaptive Bayesian scheme of Anderson uses available observations to update the Gaussian inflation distribution assigned for every state variable. The likelihood function of the inflation is computed using model-minus-data innovation statistics. A number of enhancements for this inflation scheme are proposed. To prevent excessive deflation, an inverse gamma distribution for the prior inflation is considered. A non-Gau
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2

Craney, Trevor A., and James G. Surles. "Model-Dependent Variance Inflation Factor Cutoff Values." Quality Engineering 14, no. 3 (2002): 391–403. http://dx.doi.org/10.1081/qen-120001878.

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3

Bojanic, Antonio N. "A Markov-Switching Model of Inflation in Bolivia." Economies 9, no. 1 (2021): 37. http://dx.doi.org/10.3390/economies9010037.

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The Bolivian inflation process is analyzed utilizing a time-varying univariate and multivariate Markov-switching model (TMS). With monthly data and, beginning in the late 1930s, inflation is accurately described by a univariate TMS. The intercept for the high-inflation regime is significantly higher than for the low-inflation regime and the actual inflation rate mirrors the smoothing probabilities of the Markov process. Additionally, the predicted duration of each regime closely fits the periods when the country experienced low and inordinate high inflation rates. From a long-run perspective a
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4

Daood Al-Oshaibat, Suleiman, and Hmood H. Banikhalid. "The Impact of Bank Credit on Inflation in Jordan by Using Vector Auto Regression Model: A Case Study of Jordan during 1968-2017." International Business Research 12, no. 5 (2019): 34. http://dx.doi.org/10.5539/ibr.v12n5p34.

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Previous studied revealed mixed results regarding the Banks have an influence on the inflation rate. This study aims at investigating the impact of the bank credit on the inflation rate in Jordan during the period 1968-2017 by using Vector Auto Regression Model (VAR) on the annual data. Necessary tests were conducted for this model such as Unit Root Test, Granger Causality Test, Variance Decomposition and Response Function analysis. The results reveal that there is a mutual effect between the bank credit and the inflation rate. Moreover the study states that there is an explanatory power of th
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Qasim, Tahira Bano, Hina Ali, Natasha Malik, and Malika Liaquat. "Forecasting Inflation Applying ARIMA Model with GARCH Innovation: The Case of Pakistan." Journal of Accounting and Finance in Emerging Economies 7, no. 2 (2021): 305–16. http://dx.doi.org/10.26710/jafee.v7i2.1681.

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Purpose: The research aims to build a suitable model for the conditional mean and conditional variance for forecasting the rate of inflation in Pakistan by summarizing the properties of the series and characterizing its salient features.
 Design/Methodology/Approach: For this purpose, Pakistan’s Inflation Rate is based upon the Consumer Price Index (CPI), ranging from January 1962 to December 2019 has been analyzed. Augmented Dickey Fuller (ADF) test that was used for testing the stationarity of the series. The ARIMA modeling technique is a conditional mean and GARCH model for conditional
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6

Miyoshi, Takemasa. "The Gaussian Approach to Adaptive Covariance Inflation and Its Implementation with the Local Ensemble Transform Kalman Filter." Monthly Weather Review 139, no. 5 (2011): 1519–35. http://dx.doi.org/10.1175/2010mwr3570.1.

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In ensemble Kalman filters, the underestimation of forecast error variance due to limited ensemble size and other sources of imperfection is commonly treated by empirical covariance inflation. To avoid manual optimization of multiplicative inflation parameters, previous studies proposed adaptive inflation approaches using observations. Anderson applied Bayesian estimation theory to the probability density function of inflation parameters. Alternatively, Li et al. used the innovation statistics of Desroziers et al. and applied a Kalman filter analysis update to the inflation parameters based on
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Marcoulides, Katerina M., and Tenko Raykov. "Evaluation of Variance Inflation Factors in Regression Models Using Latent Variable Modeling Methods." Educational and Psychological Measurement 79, no. 5 (2018): 874–82. http://dx.doi.org/10.1177/0013164418817803.

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A procedure that can be used to evaluate the variance inflation factors and tolerance indices in linear regression models is discussed. The method permits both point and interval estimation of these factors and indices associated with explanatory variables considered for inclusion in a regression model. The approach makes use of popular latent variable modeling software to obtain these point and interval estimates. The procedure allows more informed evaluation of these quantities when addressing multicollinearity-related issues in empirical research using regression models. The method is illus
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8

Lewis, Karen K. "Inflation risk and asset market disturbances: The mean-variance model revisited." Journal of International Money and Finance 7, no. 3 (1988): 273–88. http://dx.doi.org/10.1016/0261-5606(88)90031-9.

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9

Yu, Mei, Qian Gao, Zijian Liu, Yike Zhou, and Dan Ralescu. "A Study on the Optimal Portfolio Strategies Under Inflation." Journal of Systems Science and Information 3, no. 2 (2015): 111–32. http://dx.doi.org/10.1515/jssi-2015-0111.

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AbstractThis paper tests the inflation hedging ability of four categories of important financial assets in China: Commodity futures, real estate, gold and industry stock and select the assets that have significant inflation hedging effect. Then the authors construct the mean-variance model under the inflation factor, using the selected assets to construct the inflation hedging portfolio, solving the model and obtain the optimal investment strategy with inflation protection function. The result shows that the portfolio constructed by the model have more stable real returns and its inflation hed
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10

Pham, Van Anh. "Exchange rate pass-through into inflation in Vietnam: evidence from VAR model." Journal of Economics and Development 21, no. 2 (2019): 144–55. http://dx.doi.org/10.1108/jed-07-2019-0013.

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Purpose The purpose of this paper is to examine and analyze the exchange rate pass-through into inflation (ERPT) in Vietnam. Design/methodology/approach The paper examines and analyzes the ERPT in Vietnam by applying vector autoregression model over the period 2008‒2018. Findings The key finding of the research is that from the impulse response results, the transmission of exchange rate shocks to inflation is significant in Vietnam, and this is incomplete exchange rate pass-through. Moreover, the evidence from variance decompositions argues that exchange rate is an important factor to explain
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11

Zhou, Fang Bin, and Yun Kai Guo. "Analysis on Difference of Contaminated Normal Distribution PDF." Applied Mechanics and Materials 409-410 (September 2013): 1661–66. http://dx.doi.org/10.4028/www.scientific.net/amm.409-410.1661.

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As a very important distribution, contaminated normal distribution play a great role in data processing. The probability density function (PDF) feature of the contaminated normal distribution was investigated. The Kullback-Leibler distance is suggested for measuring PDF difference between mean shift model and variance inflation model. Numerical calculations show that the PDF difference of two kinds of model is related to mean shift parameter λ and the variance inflation factor α closely when the main distribution is the standard normal distribution and the relationship is nonlinear proportiona
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12

Babak, Olena, and Clayton V. Deutsch. "An intrinsic model of coregionalization that solves variance inflation in collocated cokriging." Computers & Geosciences 35, no. 3 (2009): 603–14. http://dx.doi.org/10.1016/j.cageo.2008.02.025.

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13

Bos, Charles S., Siem Jan Koopman, and Marius Ooms. "Long memory with stochastic variance model: A recursive analysis for US inflation." Computational Statistics & Data Analysis 76 (August 2014): 144–57. http://dx.doi.org/10.1016/j.csda.2012.11.019.

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14

Ding, Peng. "Two seemingly paradoxical results in linear models: the variance inflation factor and the analysis of covariance." Journal of Causal Inference 9, no. 1 (2021): 1–8. http://dx.doi.org/10.1515/jci-2019-0023.

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Abstract A result from a standard linear model course is that the variance of the ordinary least squares (OLS) coefficient of a variable will never decrease when including additional covariates into the regression. The variance inflation factor (VIF) measures the increase of the variance. Another result from a standard linear model or experimental design course is that including additional covariates in a linear model of the outcome on the treatment indicator will never increase the variance of the OLS coefficient of the treatment at least asymptotically. This technique is called the analysis
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15

Žagar, N., J. Tribbia, J. L. Anderson, and K. Raeder. "Balance of the Background-Error Variances in the Ensemble Assimilation System DART/CAM." Monthly Weather Review 139, no. 7 (2011): 2061–79. http://dx.doi.org/10.1175/2011mwr3477.1.

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Abstract This paper quantifies the linear mass–wind field balance and its temporal variability in the global data assimilation system Data Assimilation Research Testbed/Community Atmosphere Model (DART/CAM), which is based on the ensemble adjustment Kalman filter. The part of the model state that projects onto quasigeostrophic modes represents the balanced state. The unbalanced part corresponds to inertio-gravity (IG) motions. The 80-member ensemble is diagnosed by using the normal-mode function expansion. It was found that the balanced variance in the prior ensemble is on average about 90% of
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16

Lehmann, Rüdiger, Michael Lösler, and Frank Neitzel. "Mean Shift versus Variance Inflation Approach for Outlier Detection—A Comparative Study." Mathematics 8, no. 6 (2020): 991. http://dx.doi.org/10.3390/math8060991.

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Outlier detection is one of the most important tasks in the analysis of measured quantities to ensure reliable results. In recent years, a variety of multi-sensor platforms has become available, which allow autonomous and continuous acquisition of large quantities of heterogeneous observations. Because the probability that such data sets contain outliers increases with the quantity of measured values, powerful methods are required to identify contaminated observations. In geodesy, the mean shift model (MS) is one of the most commonly used approaches for outlier detection. In addition to the MS
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17

Sheefeni, Johannes, and Matthew Ocran. "Exchange rate pass-through to domestic prices in Namibia: SVAR evidence." Journal of Economic and Financial Sciences 7, no. 1 (2014): 89–102. http://dx.doi.org/10.4102/jef.v7i1.132.

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This article investigates exchange rate pass-through to domestic prices in Namibia. The study covers the period of 1993:Q1 – 2011:Q4, and employed the impulse response functions and variance decompositions obtained from a structural vector autoregressive model. The results from the impulse response functions show that there is a high and long-lasting effect from changes in exchange rates to inflation in Namibia, or high exchange rate pass-through into domestic inflation. The results from the forecast error variance decompositions also reflect that changes in the price level evolve endogenously
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18

Karanasos, Menelaos, and Stefanie Schurer. "Is the Relationship between Inflation and Its Uncertainty Linear?" German Economic Review 9, no. 3 (2008): 265–86. http://dx.doi.org/10.1111/j.1468-0475.2008.00433.x.

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Abstract We use parametric power ARCH models of the conditional variance of inflation to model the relationship between inflation and its uncertainty using monthly data for Germany, the Netherlands and Sweden over a period ranging from 1962 to 2004. For all three countries inflation significantly raises inflation uncertainty as predicted by Friedman. Increased uncertainty affects inflation in all countries but not in the same manner. For Sweden we find a negative impact in accordance with the Holland hypothesis, whereas for Germany and the Netherlands we find the opposite in support of the Cuk
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19

Hasui, Kohei. "A NOTE ON ROBUST MONETARY POLICY AND NON-ZERO TREND INFLATION." Macroeconomic Dynamics 24, no. 6 (2018): 1574–94. http://dx.doi.org/10.1017/s1365100518000883.

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This paper studies how model uncertainty influences economic fluctuation when trend inflation is high. We introduce Hansen and Sargent’s [(2008) Robustness, Princeton University Press] robust control techniques into a New Keynesian model with non-zero trend inflation. We reveal the following three points. First, we find that robust monetary policy responds more aggressively. This aggressiveness increases with trend inflation. Second, as the trend inflation rises, the response of macroeconomic variables is larger under robust policy. Third, stronger robustness tends to lead to indeterminate equ
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20

Saleem, Nadia. "Measuring Volatility of Inflation in Pakistan." LAHORE JOURNAL OF ECONOMICS 13, no. 2 (2008): 99–128. http://dx.doi.org/10.35536/lje.2008.v13.i2.a6.

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The available evidence in Pakistan suggests that inflation is a monetary phenomena. This paper examines the relationship between the determinants of inflation and its volatility by using monthly data for 1990:M1-2007:M5. The determinants of inflation are estimated by a VAR analysis, which shows that inflation, the interest rate and money supply move together. A VAR model assumes constant error variance. We relaxed this assumption by employing an ARCH/GARCH model and conclude that inflation is volatile in nature. For measuring the qualitative nature of the inflationary process we used an EGARCH
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21

M. N, Ripdian Nisa, Banatul Hayati, and Edy Yusuf A. G. "Effectiveness of Monetary Policy Transmission Mechanism in Indonesia." JEJAK 11, no. 1 (2018): 189–206. http://dx.doi.org/10.15294/jejak.v11i1.12385.

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This research aimed to analyse monetary mechanism effectivity to manage inflation in Indonesia through interest rate channel, credit channel, and expectation inflation channel. The research used Vector Error Correction Model (VECM) to analyze effectiveness of monetary policy transmission mechanism in Indonesia. The most effective channel was measured by result of Impulse Response Function and Variance Decomposition. They are: (1). The fastest time lag needed since the shock of monetary instruments (rSBI) until the realization of final target of monetary policy (inflation). (2). How strong the
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22

Ulfatul, Ilma. "The Analysis of Monetary Transmission Mechaniscm by Expectation Patterns in Influencing the Inflation." Economics Development Analysis Journal 6, no. 4 (2018): 412–19. http://dx.doi.org/10.15294/edaj.v6i4.22291.

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Bank Indonesia set inflation targeting framework from 1 July 2005 by publicizing the inflation target or forward inflation to the public. However, the phenomenon show that most of the actual inflation of Indonesia is not in accordance with inflation targeting that have been set by Bank Indonesia. The purpose of this research is to analyze and know the flow of monetary policy transmission mechanism of expectation line in influencing inflation, to analyze and to know the influence of long-term and short-term and the shocks of interest rate, exchange rate, inflation expectations, output gap and G
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23

Mehibel, Samer, and Yacine Belarbi. "Inflation Dynamics in Algeria." Journal of Economics and Behavioral Studies 9, no. 6 (2018): 174–87. http://dx.doi.org/10.22610/jebs.v9i6.2014.

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In thispaper, we analyze Inflation Dynamics in Algeria between 2002 and 2016. We use a Vector Auto Regressive model (VAR), impulse response functions (IRF) and variance error decomposition (VDC) to uncover possible links between public spending component sand inflation. Wetest for the sources and dynamics of inflation in Algeria by focusing on public spending, since they are expected to exert a strong influence on the aggregate demand and hence inflation. According to the results we found, inflation in Algeria is persistent; shocks are lasting longer and having impact on the future inflation p
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24

Kaplan, Fatih, and Sule Gungor. "The Relationship Between Money Supply, Interest Rate and Inflation Rate: an Endogeneity-Exogeneity Approach." European Scientific Journal, ESJ 13, no. 1 (2017): 30. http://dx.doi.org/10.19044/esj.2017.v13n1p30.

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After the 2008 Financial Crisis, The Central Bank is Turkey as well as many countries, has implemented a policy of increasing the money supply. It is a known fact that the changes in the money supply are considerable extent determinative in interest rate and inflation rate such as orientations of macro economics variables. The purpose of this study is to investigate the relationship between money supply, interest rate and inflation rate in Turkey after the 2008 Financial Crisis. In accordance with this purpose, 2008:1- 2015:12 period money supply, interest rate and inflation rate monthly data
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25

Goyal, Ashima, and Abhishek Kumar. "A DSGE Model-Based Analysis of the Indian Slowdown." Journal of International Commerce, Economics and Policy 11, no. 01 (2020): 2050004. http://dx.doi.org/10.1142/s1793993320500040.

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A New Keynesian Dynamic Stochastic General Equilibrium (DSGE) model with habit persistence used to examine the US slowdown is also used to analyze the contribution of basic demand and supply shocks to the Indian slowdown. Kalman filter-based maximum likelihood estimation is undertaken with Indian output, inflation and interest rate data. First, our model based output gap tracks the statistical Hodrick–Prescott filter-based output gap well. Second, comparison of estimated parameters, impulse responses and forecast error variance decomposition between India and the US brings out the differences
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26

Białek, Jacek. "Basic Statistics of Jevons and Carli Indices under the GBM Price Model." Journal of Official Statistics 36, no. 4 (2020): 737–61. http://dx.doi.org/10.2478/jos-2020-0037.

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AbstractMost countries use either the Jevons or Carli index for the calculation of their Consumer Price Index (CPI) at the lowest (elementary) level of aggregation. The choice of the elementary formula for inflation measurement does matter and the effect of the change of the index formula was estimated by the Bureau of Labor Statistics (2001). It has been shown in the literature that the difference between the Carli index and the Jevons index is bounded from below by the variance of the price relatives. In this article, we extend this result, comparing expected values and variances of these sa
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27

Zapata, Juan, and Juan Ciro. "The communication effects on inflation forecast errors: Empirical evidence from Colombia." Panoeconomicus, no. 00 (2020): 16. http://dx.doi.org/10.2298/pan180101016z.

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The purpose of this article is to explore the central bank's ability to management inflation forecast errors in Colombia. We present empirical evidence based on the Colombian experience with data from the period of 2008 to 2020. The communication channel selected for analysis is the press releases. The empirical evidence is divided into three steps: (i) regression analysis using an EGARCH model, (ii) use of VAR models, and (iii) variance decomposition analysis. The communications effects are significant for several months and that close to half of the forecast error variance can be explained b
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28

Cosimano, Thomas F., and Dennis W. Jansen. "Estimates of the Variance of U. S. Inflation Based upon the ARCH Model: Comment." Journal of Money, Credit and Banking 20, no. 3 (1988): 409. http://dx.doi.org/10.2307/1992266.

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29

Yao, Haixiang, Zhou Yang, and Ping Chen. "Markowitz’s mean–variance defined contribution pension fund management under inflation: A continuous-time model." Insurance: Mathematics and Economics 53, no. 3 (2013): 851–63. http://dx.doi.org/10.1016/j.insmatheco.2013.10.002.

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30

Abd. Majid, M. Shabri. "Re-Examining the Finance-Growth Nexus: Empirical Evidence from Indonesia." Gadjah Mada International Journal of Business 9, no. 2 (2007): 137. http://dx.doi.org/10.22146/gamaijb.5597.

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This paper empirically examines the short- and long-run relationships between financial development and economic growth during the post-1997 financial crisis in Indonesia by employing a battery of times-series techniques, such as Autoregressive Dis-tributed Lag (ARDL) model, vector error correction model (VECM), variance decompositions (VDCs), and impulse-response functions (IRFs). Based on the ARDL (2, 0, 1, 2) model, the study finds that there exists a long-run equilibrium between economic growth and financial depth, share of investment, and inflation. In the long run, inflation is found to
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31

Al-Ezzee, Ibrahem H. "Drivers of Inflation in the Economy of Bahrain." International Journal of Economics and Finance 8, no. 3 (2016): 178. http://dx.doi.org/10.5539/ijef.v8n3p178.

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<p>The study tries to recognize the macroeconomic variables responsible for inflation in Bahrain during the period 1980-2010. For this purpose, co-integration test were used in the empirical analysis. Using Augmented Dickey-Fuller (ADF) Phillips Perron (PP) tests, the variables of the study revealed to be integrated of the order one 1(1) at first difference. Cointegration test was used to state the existence or otherwise of a cointegrating vector in the variables. Trace and Maximum Eigen test value point out co-integration at 5% level of significance pointing to the fact that the variabl
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32

Minamide, Masashi, and Fuqing Zhang. "Adaptive Observation Error Inflation for Assimilating All-Sky Satellite Radiance." Monthly Weather Review 145, no. 3 (2017): 1063–81. http://dx.doi.org/10.1175/mwr-d-16-0257.1.

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An empirical flow-dependent adaptive observation error inflation (AOEI) method is proposed for assimilating all-sky satellite brightness temperatures through observing system simulation experiments with an ensemble Kalman filter. The AOEI method adaptively inflates the observation error when the absolute difference (innovation) between the observed and simulated brightness temperatures is greater than the square root of the combined variance of the uninflated observational error variance and ensemble-estimated background error variance. This adaptive method is designed to limit erroneous analy
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33

Yang, Peng. "Robust Time-Consistent Portfolio Selection for an Investor under CEV Model with Inflation Influence." Mathematical Problems in Engineering 2020 (June 17, 2020): 1–14. http://dx.doi.org/10.1155/2020/2359135.

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A robust time-consistent optimal investment strategy selection problem under inflation influence is investigated in this article. The investor may invest his wealth in a financial market, with the aim of increasing wealth. The financial market includes one risk-free asset, one risky asset, and one inflation-indexed bond. The price process of the risky asset is governed by a constant elasticity of variance (CEV) model. The investor is ambiguity-averse; he doubts about the model setting under the original probability measure. To dispel this concern, he seeks a set of alternative probability meas
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34

Whitaker, Jeffrey S., and Thomas M. Hamill. "Evaluating Methods to Account for System Errors in Ensemble Data Assimilation." Monthly Weather Review 140, no. 9 (2012): 3078–89. http://dx.doi.org/10.1175/mwr-d-11-00276.1.

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Abstract Inflation of ensemble perturbations is employed in ensemble Kalman filters to account for unrepresented error sources. The authors propose a multiplicative inflation algorithm that inflates the posterior ensemble in proportion to the amount that observations reduce the ensemble spread, resulting in more inflation in regions of dense observations. This is justified since the posterior ensemble variance is more affected by sampling errors in these regions. The algorithm is similar to the “relaxation to prior” algorithm proposed by Zhang et al., but it relaxes the posterior ensemble spre
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35

Astuti, Cindy Cahyaning, and Angga Dwi Mulyanto. "Estimation Parameters And Modelling Zero Inflated Negative Binomial." CAUCHY 4, no. 3 (2016): 115. http://dx.doi.org/10.18860/ca.v4i3.3656.

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Regression analysis is used to determine relationship between one or several response variable (Y) with one or several predictor variables (X). Regression model between predictor variables and the Poisson distributed response variable is called Poisson Regression Model. Since, Poisson Regression requires an equality between mean and variance, it is not appropriate to apply this model on overdispersion (variance is higher than mean). Poisson regression model is commonly used to analyze the count data. On the count data type, it is often to encounteredd some observations that have zero value wit
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36

Zubaidi Baharumshah, Ahmad, and Siew-Voon Soon. "Inflation, inflation uncertainty and output growth: what does the data say for Malaysia?" Journal of Economic Studies 41, no. 3 (2014): 370–86. http://dx.doi.org/10.1108/jes-05-2012-0073.

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Purpose – The purpose of this paper is to examine the causal relationships between inflation, output growth and their uncertainties in Malaysia. Design/methodology/approach – The modeling approach allows for structural breaks to avoid the masking of specific impacts. Findings – Based on the asymmetric Generalized Autoregressive Conditional Heteroskedasticity model, the paper found strong evidence favoring a positive effect of a change in the inflation uncertainty as predicted by the Friedman-Ball hypothesis. In addition, inflation (inflation uncertainty) has direct (indirect) negative effect o
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37

Hodyss, Daniel, Justin G. McLay, Jon Moskaitis, and Efren A. Serra. "Inducing Tropical Cyclones to Undergo Brownian Motion: A Comparison between Itô and Stratonovich in a Numerical Weather Prediction Model." Monthly Weather Review 142, no. 5 (2014): 1982–96. http://dx.doi.org/10.1175/mwr-d-13-00299.1.

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Abstract Stochastic parameterization has become commonplace in numerical weather prediction (NWP) models used for probabilistic prediction. Here a specific stochastic parameterization will be related to the theory of stochastic differential equations and shown to be affected strongly by the choice of stochastic calculus. From an NWP perspective the focus will be on ameliorating a common trait of the ensemble distributions of tropical cyclone (TC) tracks (or position); namely, that they generally contain a bias and an underestimate of the variance. With this trait in mind the authors present a
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Wu, Xinrong. "Improving EnKF-Based Initialization for ENSO Prediction Using a Hybrid Adaptive Method." Journal of Climate 29, no. 20 (2016): 7365–81. http://dx.doi.org/10.1175/jcli-d-16-0062.1.

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Abstract Probabilistic forecasts, which are usually initialized by an ensemble Kalman filter (EnKF), are known to be better than deterministic (or one member) forecasts for the El Niño–Southern Oscillation (ENSO) phenomenon. Because of sampling errors caused by a finite ensemble and the errors related to model biases associated with the physical parameterizations, dynamic core, model resolution, and so on, a state-of-the-art inflation method is commonly used in the standard EnKF to increase the prior variance so as to avoid filter divergence. However, the optimal inflation factor is almost pro
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Berardi, Andrea, and Alberto Plazzi. "Inflation Risk Premia, Yield Volatility, and Macro Factors." Journal of Financial Econometrics 17, no. 3 (2018): 397–431. http://dx.doi.org/10.1093/jjfinec/nby004.

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Abstract We incorporate a latent stochastic volatility factor and macroeconomic expectations in an affine model for the term structure of nominal and real rates. We estimate the model over 1999–2016 on U.S. data for nominal and TIPS yields, the realized and implied volatility of T-bonds, and survey forecasts of GDP growth and inflation. We find relatively stable inflation risk premia averaging at 40 basis points at the long-end, and which are strongly related to the volatility factor and conditional mean of output growth. We also document real risk premia that turn negative in the post-crisis
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Hidayah Mohamed Isa, Noor, Mahmod Othman, and Samsul Ariffin Abdul Karim. "Multivariate Matrix for Fuzzy Linear Regression Model to Analyse The Taxation in Malaysia." International Journal of Engineering & Technology 7, no. 4.33 (2018): 78. http://dx.doi.org/10.14419/ijet.v7i4.33.23490.

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A multivariate matrix is proposed to find the best factor for fuzzy linear regression (FLR) with symmetric triangular fuzzy numbers (TFNs). The goal of this paper is to select the best factor influence tax revenue among four variables. Eighteen years’ data of the variables from IndexMundi and World Bank Data. It is found that the model is successfully explained between independent variables and response variable. It is notices that sixty-six percent of the variance of tax revenue is explained by Gross Domestic Product, Inflation, Unemployment and Merchandise Trade. The introduction of multivar
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Kemda, Lionel Establet, Chun-Kai Huang, and Knowledge Chinhamu. "Value-at-risk for the USD/ZAR exchange rate: The Variance-Gamma model." South African Journal of Economic and Management Sciences 18, no. 4 (2015): 551–66. http://dx.doi.org/10.4102/sajems.v18i4.966.

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A country’s level of exchange risk is closely linked to its financial stability, on a macro-economic scale. South African exchange rates, in particular, have a significant impact on imports, inflation, consumer prices and monetary policies. Consequently, it is imperative for economists and investors to assess accurately the associated exchange risks. Exchange rates, like most financial time series, are leptokurtic and contradict the classical Gaussian assumption. We therefore introduce subclasses of the generalised hyperbolic distribution as alternative models and contrast these with the norma
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42

Wardani, Mita Pradnya, Regina Niken W., and Agus Lutfi. "Dampak Harga Minyak Dunia Terhadap Jumlah Uang Beredar di Indonesia Tahun 2005.Q1-2016.Q4." e-Journal Ekonomi Bisnis dan Akuntansi 6, no. 1 (2019): 91. http://dx.doi.org/10.19184/ejeba.v6i1.11110.

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Policies taken by the government and the central bank greatly determine the size of the money supply. World oil prices play a role in increasing the money supply through inflation. The purpose of this study is to find out the most effective policy in controlling the money supply by the public, using the Vector Autoregressive (VAR) model to estimate the variables in the study. The estimation of the impulse response function and also the variance decomposition which describes how and how much influence the shock from the amount of money supply. The VAR estimation shows that the money supply is m
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43

Mammen, Enno, Jens Perch Nielsen, Michael Scholz, and Stefan Sperlich. "Conditional Variance Forecasts for Long-Term Stock Returns." Risks 7, no. 4 (2019): 113. http://dx.doi.org/10.3390/risks7040113.

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In this paper, we apply machine learning to forecast the conditional variance of long-term stock returns measured in excess of different benchmarks, considering the short- and long-term interest rate, the earnings-by-price ratio, and the inflation rate. In particular, we apply in a two-step procedure a fully nonparametric local-linear smoother and choose the set of covariates as well as the smoothing parameters via cross-validation. We find that volatility forecastability is much less important at longer horizons regardless of the chosen model and that the homoscedastic historical average of t
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44

Lee, Siew-Peng, Mansor Isa, and Noor Azryani Auzairy. "The relationships between time deposit rates, real rates, inflation and risk premium." Journal of Islamic Accounting and Business Research 11, no. 5 (2020): 1033–53. http://dx.doi.org/10.1108/jiabr-01-2018-0010.

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Purpose The purpose of this paper is to investigate the influence of the real interest rates, inflation and risk premium on the time deposit rates of banks in the dual banking system in Malaysia. Design/methodology/approach The data consists of 1-, 6- and 12-month average time deposit rates of conventional and Islamic banks over the period of January 2000 to June 2017. The cointegration methodologies are used to explore links between the time deposit rates, real rates, inflation and risk premium. The causality tests to test causality linkages between pairs of variables are also applied. The ge
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45

Kelly, R. J. "GDOP, Ridge Regression and the Kalman Filter." Journal of Navigation 43, no. 03 (1990): 409–27. http://dx.doi.org/10.1017/s0373463300014041.

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Multicollinearity and its effect on parameter estimators such as the Kalman filter is analysed using the navigation application as a special example. All position-fix navigation systems suffer loss of accuracy when their navigation landmarks are nearly collinear. Nearly collinear measurement geometry is termed the geometric dilution of position (GDOP). Its presence causes the errors of the position estimates to be highly inflated. In 1970 Hoerl and Kennard developed ridge regression to combat near collinearity when it arises in the predictor matrix of a linear regression model. Since GDOP is m
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Ohyver, Margaretha. "Metode Regresi Ridge Untuk Mengatasi Kasus Multikolinear." ComTech: Computer, Mathematics and Engineering Applications 2, no. 1 (2011): 451. http://dx.doi.org/10.21512/comtech.v2i1.2782.

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Multicolinear is a case that occurs in multi-linear regression analysis. Using multicolinear, it will be difficult to separate the influence of each independent variable towards the response variables. It also occurs in a farm production like cabbage. To solve this problem, Ridge regression method is used. This research aims to obtain a Ridge regression model to solve the multicolinear case. By using this method, the alleged regression coefficient is obtained by variance inflation factor less than ten for six free variables.
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Rodríguez Arana, Alejandro. "Limited Information and the Relation Between the Variance of Inflation and the Variance of Output in a New Keynesian Perspective." Revista Mexicana de Economía y Finanzas 14, PNEA (2019): 541–57. http://dx.doi.org/10.21919/remef.v14i0.422.

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The objective of this paper is to analyze the effects on welfare of a monetary policy that establishes the reference interest rate at discrete intervals of time. The hypothesis is that because there is uncertainty about various disturbances that will occur in the period in which the referential interest rate is established, this can cause a loss of social welfare. To analyze the problem, a model is proposed where the central bank minimizes a loss function. When there is perfect certainty, an efficient frontier between the variances of inflation and output is reached. With uncertainty the resul
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Keswani, Sarika, and Bharti Wadhwa. "An Empirical Analysis on Association Between Selected Macroeconomic Variables and Stock Market in the Context of BSE." Indian Economic Journal 66, no. 1-2 (2018): 170–89. http://dx.doi.org/10.1177/0019466219876492.

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The role of macroeconomic variables cannot be ignored because it plays a very important role in shaping the economy of any country, irrespective of whether it is developing, underdeveloped or developed. The macroeconomic variables were disposable income (DI), government policies (GP), inflation rate (INF), interest rate (IR), exchange rate (ER) and stock price. Monthly data of 10 years were used, that is, from April 2006 to March 2016. Analyses of augmented Dickey–Fuller test, preliminary tests, stability tests, cointegration, vector error correction model (VECM) variance decomposition analysi
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Lisani, Nurul, Raja Masbar, and Vivi Silvia. "Inflation-Unemployment Trade-Offs In ASEAN-10." Signifikan: Jurnal Ilmu Ekonomi 9, no. 2 (2020): 241–56. http://dx.doi.org/10.15408/sjie.v9i2.16346.

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This study empirically explores the nature of inflation-unemployment dynamic causal relationships both in the short and long-run in the ASEAN-10 over the 1989-2018 period. Based on the panel cointegration test, the study documented a long-run equilibrium between inflation and unemployment. Using the Vector Error Correction Model (VECM) analysis, the study found an insignificant inflation-unemployment relationship in the short-run. However, in the long-run, inflation is found to affect the unemployment rate positively. Our results from the Variance Decompositions (VDCs) analysis also supported
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Sun, Jingyun, Zhongfei Li, and Yongwu Li. "Equilibrium Investment Strategy for DC Pension Plan with Inflation and Stochastic Income under Heston’s SV Model." Mathematical Problems in Engineering 2016 (2016): 1–18. http://dx.doi.org/10.1155/2016/2391849.

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We consider a portfolio selection problem for a defined contribution (DC) pension plan under the mean-variance criteria. We take into account the inflation risk and assume that the salary income process of the pension plan member is stochastic. Furthermore, the financial market consists of a risk-free asset, an inflation-linked bond, and a risky asset with Heston’s stochastic volatility (SV). Under the framework of game theory, we derive two extended Hamilton-Jacobi-Bellman (HJB) equations systems and give the corresponding verification theorems in both the periods of accumulation and distribu
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