Medical Net Discount Rates:

Save this PDF as:
 WORD  PNG  TXT  JPG

Size: px
Start display at page:

Download "Medical Net Discount Rates:"

Transcription

1 Medical Net Discount Rates: An Investigation into the Total Offset Approach Andrew G. Kraynak Fall 2011 COLLEGE OF THE HOLY CROSS ECONOMICS DEPARTMENT HONORS PROGRAM

2 Motivation When estimating the cost of future medical care, forensic economists (FEs) use a medical cost net discount rate (MNDR), constructed with a growth rate and a discount rate, to adjust for inflation and investment rates. A discount rate allows a court to award compensation for damages to a victim in a lump sum, instead of drawing out the award by requiring the liable party to pay for the victim s medical costs year after year. The medical component of the Consumer Price Index (MCPI) is used as the growth rate when calculating the net discount rate for court awards that involve compensation for future medical care. The MCPI is used in conjunction with an interest rate in order to calculate the MNDR. There is, however, no consensus among FEs on which interest should be used for MNDRs. An argument in favor of the use of shorter-term interest rates comes from a frequently cited US Supreme Court ruling on lost future earnings. It dictates the use of an interest rate that is both the best and safest (Jones and Laughlin v. Pfeifer pg. 537). Although these terms are somewhat contradictory, the ruling later describes the interest rate that should be used in discounting as simply the safest. This emphasis on safety provides a basis for using securities of shorter duration with lower returns. While the Pfeifer ruling was made in regards to lost earnings, the case can be extended to provide a principle for discounting awards for future medical costs. Ireland and Tucek (2011) have assembled tables with historical averages of discount rates constructed with five different interest rates (3-Month, 1-Year, and 10-Year US Treasury securities, corporate AAA bonds, and municipal bonds). The broad spectrum of interest rates included in their tables attests to the diversity in opinion of FEs on which interest rate is proper for MNDRs. The historical averages of MNDRs constructed with 3-Month and 1-Year US 2

3 Treasury securities are approximately within one half of one percent of zero for their thirty year averages, which use data from 1981 to Historical averages, however, may not be the best predictor of future MNDRs. Ewing, Payne, and Piette (2001) use time series analysis to look at the MNDR during the period from January 1981 to May 2000, using monthly data for both the growth rate (MCPI) and the interest rate (Treasury notes and bonds with 1-, 2-, 3-, and 10-year maturities). They reject the total offset approach, which states that the growth rate and interest are equal over time: Regardless of the discount rate used to compute the MNDR, we found evidence against the use of the total offset method (Ewing, Payne, and Piette 2001). Their study also uses the Augmented Dickey- Fuller (ADF) test to establish the stationarity of the MNDR. Gelles and Johnson (1996) describe a regime change in the Federal Reserve s monetary policy that structurally shifted post-1980 interest rates. Ewing, Payne, and Piette (2001) begin their data series after the regime change in order to avoid the Federal Reserve s policy shift. Furthering the time series analysis, Sen and Gelles (2006) use a Crash Model (following Zivot and Andrews, 1992) and find the MNDR to be trend-break stationary over the period from January 1980 to January Using the MCPI and a 1-year Treasury note, Sen and Gelles find that the MNDR has a break-point in January When looking at historical averages of MNDRs, a break-point date has the same effect as a regime change in the Federal Reserve: forensic practitioners should use the estimated trend function in the post-break period to forecast the medical net discount rates (Sen and Gelles 2006). 1 Only the 1-year Treasury bill was used by Sen and Gelles (2006) to establish break-dates for MNDRs that were constructed with various medical Consumer Price Subindexes. This study employs the MNDR constructed with the medical care CPI, and uses its break-date of January 1994 for tests on the 3-month MNDR, 6-month MNDR, and 1-year MNDR. Ideally, break-dates would be estimated using the Crash Model for each variation of the MNDR in this study, but a Crash Model was beyond the scope of this paper. 3

4 Since the study by Ewing, Payne, and Piette (2001), a full decade s worth of MCPI and interest rate data has become available. This new decade of data contains MNDRs that are, on average, lower in value than MNDRs in previous years. Additionally, the 3-Month and 6-Month US Treasury securities, which have lower rates of return than the 1-Year US Treasury security, were not included in the study by Ewing, Payne, and Piette (2001). In light of these facts, the question of total offset seems to require further examination. This study seeks to build upon the framework of Ewing, Payne, and Piette (2001) by first replicating their results using data from January 1980 to May 2000 (referred to henceforth as the period). I will then add to their work by extending their data set to include MNDRs into 2011 (henceforth the Extended period). Additionally, this study will employ the 3-Month and 6-Month Treasury bills to inquire into the question of whether the total offset approach can be justified with the MNDR based on Treasury securities of shorter duration (i.e. the safest ). Finally, I will use the January 1994 break-date established by Sen and Gelles (2006) to compare the analysis of the period to the period (Early Split period) and the period (Late Split Period). Figure 1 shows the 3-Month, 6-Month, and 1-Year MNDR series over the Extended period. In order to replicate a part of the study by Ewing, Payne, and Piette (2001), MNDRs were constructed using the percent change in the medical component of the Consumer Price Index (MCPI) and the rate of return on the 1-Year Treasury Security. The data were collected on a monthly basis beginning in January 1980 and ending in August Data for the percent change in the MCPI were calculated based on the percent change of one month from the same month in the previous year. Data for rates of the constant maturity 1-Year Treasury Securities were obtained from the St. Louis Federal Reserve s FRED series (Federal Reserve Economic 4

5 Data) and converted to a bond yield basis. 2 The simple MNDR calculation was used by Ewing, Payne, and Piette (2001), and this study employs the same formula for only the 1-Year MNDR in an effort to make the results directly comparable to several of the findings by Ewing, Payne and Piette (2001). Simple MNDR = r g Figure 1 * All MNDRs were constructed using the Complex MNDR calculation and are expressed in terms of percent. MNDR using the 1-Year Constant Maturity Treasury Security The rate of return on the constant maturity 1-Year Treasury security is used as the interest rate (r), and the percent change in the MCPI is used as the growth rate (g). When these two rates 2 The Treasury Department reports that CMT yields are read directly from the Treasury s daily yield curve and represent bond equivalent yields for securities that pay semiannual interest, which are expressed on a simple annualized basis. I converted these interest rates to a bond-yield basis. 5

6 are equal over time, the MNDR will be zero and the total offset approach could be justified. To test for the Total Offset approach, a t-test was performed separately on the, Extended, and Split periods. By simply regressing the MNDR on a constant, the null hypothesis that the MNDR is zero was tested against the alternative hypothesis that the MNDR is not equal to zero. If the null hypothesis is rejected then the total offset approach cannot be justified for the MNDR constructed with the 1-Year Treasury Security. Table 1 shows the results of the t-test for the different periods. Table 1 Test for Total Offset of 1-Year MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) Constant T-Statistic P-Value The t-statistic for the period matches the results of Ewing, Payne, and Piette (2001), and I was similarly able to reject the null hypothesis of total offset for all time periods except the Late Split, from February 1994 to August The Late Split period produced a negative constant and an insubstantial t-statistic, meaning that MNDR is not statistically different from zero. The use of total offset approach could, therefore, be justified based on the Late Split period. These results were found to be robust with the more complex formula (described below) 3 Ewing, Payne, and Piette (2001) report a t-statistic of , and the small difference between the t- statistics is thought to be because of data revisions in the MCPI subsequent to publication of their article. 6

7 for MNDR and can be found in the appendix. As suggested by Sen and Gelles (2006), the Late Split period is most relevant in terms of usefulness for FEs because it does not include inappropriate MNDRs. A simple test for the total offset approach, however, does not justify the use of zero as the MNDR. Historical MNDR series are only relevant to the projection of a future MNDR if the series exhibits some type of stationarity over time. Stationarity in time-series analysis means that a series exhibits mean-reversion after exogenous shocks. A series that does not revert back to its mean over time but rather seems to experience random upward and downward movement is referred to as a random walk or nonstationary series. Historical MNDRs are only useful if the series is stationary around zero, an historical mean, or a trend function. Otherwise, future MNDRs would be independent of previous MNDRs, making professional forecasts and current values for the interest and growth rates perhaps more accurate predictors in determining future MNDRs. An ADF test was conducted on the 1-Year MNDR series to determine if there is a unit root. The presence of a unit root indicates that the series is nonstationary and exhibits a random walk. The test was separately conducted on each of the following periods:, Extended, Early Split, and Late Split. The null hypothesis of the ADF test is that the series has a unit root (i.e. is not stationary). Subsequently, rejection of the null hypothesis implies stationarity and that the historical series of MNDRs are relevant for future MNDR estimations. The ADF test produces a τ-statistic (tau-statistic) that has a different distribution than an ordinary t-statistic, and the one-sided P-values for the ADF statistic must be used as provided by MacKinnon (1996). Table 2 reports the τ-statistic and the P-value for the ADF test. 7

8 Table 2 Test for Stationarity (Augmented Dickey-Fuller*) of 1-Year MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) τ-statistic P-Value * A time trend was not included because of the a priori hypothesis of Total Offset. The number of lagged differences included in the ADF test was determined by the Modified Aikaike s Information Criterion with a maximum number of lags set at three. The appendix shows the number of lags used for each test. The Extended period is stationary with a P-value below five percent, but for the, Early Split, and Late Split periods the null hypothesis of nonstationarity cannot be rejected. The result of stationarity in Ewing, Payne, and Piette (2001) was not upheld for the 1- Year MNDR because a different number of lagged variables was used in this study s ADF test. 4 MNDR using the 6-Month Constant Maturity Treasury Security MNDRs were constructed using the percent change in the MCPI and the rate of return on the 6-Month Constant Maturity Treasury Security. The data series was collected on a monthly basis from January 1980 to August 2011 and converted in the same way as the MCPI and 1-Year Constant Maturity Treasury Security in the previous section. The MNDR based on the 6-Month Treasury Security was constructed with the more complex and accurate formula for the MNDR. 4 The results from Ewing, Payne, and Piette (2001) were replicated using their specification of three laggeddifference variables. This ADF test yielded a τ-statistic of with a P-value of , making the MDNR series marginally (10% level) significant. 8

9 Ewing, Payne, and Piette (2001) did not look at MNDRs using interest rates with durations of less than one year, and this study will construct these MNDRs using the complex MNDR calculation. Complex MNDR = (r g)/(1+g) The interest rate (r) is the rate of return on the constant maturity 6-Month Treasury Security, and the growth rate (g) is the percent change in the MCPI. The more complex MNDR formula does not change the conclusion that when r and g are equal over time, the MNDR will be zero and the total offset approach could be justified. Again, a simple t-test was performed to test for the total offset approach by regressing the MNDR on a constant with the null hypothesis that the MNDR is zero. The t-test was performed separately on each of the periods in Table 3. Table 3 Test for Total Offset of 6-Month MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) Constant T-Statistic P-Value The total offset approach is rejected for the and Late Split periods. However, the Late Split period has a negative constant, suggesting the use of negative discounting (i.e. more than offset). The constant for the Early Split period is only marginally (10% level) significantly different from zero, and the MNDR for the Extended period has a constant that is not statistically different from zero. Therefore, total offset approach could be justified for the MNDR based on the Extended and the Early Split periods. 9

10 Sen and Gelles (2006) find evidence to suggest that their post-break period is the most relevant period for FEs, and Table 3 indicates a negative MNDR for the Late Split period (i.e. more than total offset). With the 6-Month Treasury Security, the result of a negative MNDR makes intuitive sense because the MNDR using the 1-Year Treasury Security, constructed with a larger interest rate, was found to be zero in the previous section for the Late Split period. In order to justify the use of the total offset (or more than total offset) approach, the series must exhibit stationarity over time. An ADF test was conducted on the 6-Month MNDR series with the customary null hypothesis of nonstationarity. The test was conducted on each of the periods separately, and the resulting τ-statistics and MacKinnon (1996) P-values appear in Table 4. Table 4 Test for Stationarity (Augmented Dickey-Fuller*) of 6-Month MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) τ-statistic P-Value * A time trend was not included because of the a priori hypothesis of Total Offset. The number of lagged differences included in the ADF test was determined by the Modified Aikaike s Information Criterion with a maximum number of lags set at three. The appendix shows the number of lags used for each test. The MNDR for the Extended period is stationary with a P-value below five percent. Nonstationarity cannot be rejected for the, Early Split, and Late Split periods. Therefore, the MNDR for these three periods are not mean-reverting around a constant, and historical data do not help predict their future values. 10

11 For the Extended series, the MNDR based on the 6-Month Treasury Security is not statistically different from zero and is stationary. Therefore, this finding justifies the use of the total offset approach based on the MNDRs over the Extended period. MNDR using the 3-Month Constant Maturity Treasury Security MNDRs were constructed using the percent change in the MCPI and the rate of return on the 3-Month Constant Maturity Treasury Security. The data series was collected over the same dates and converted as described in the previous sections. Performing a simple t-test, the total offset approach was tested with a regression of the MNDR on a constant with the null hypothesis that the MNDR is zero. Table 5 shows the results of the test for each series. Table 5 Test for Total Offset of 3-Month MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) Constant T-Statistic P-Value The total offset approach is rejected for the MNDR over the and Late Split periods. However, the MNDR for the Late Split period has a negative constant which suggests the use of negative discounting (i.e. more than offset). The Extended and Early Split MNDRs have constants that are not statistically different from zero, and as a result, the total offset approach could be justified based on both of the series. Sen and Gelles (2006) find evidence to suggest that their post-break period is the most relevant period for FEs, and the results in Table 5 indicate the use of a negative MNDR 11

12 and imply more than total offset. The constant for Late Split series of the 3-Month MNDR is smaller (i.e. more negative) than both the results from the 1-Year and 6-Month MNDRs, which makes intuitive sense. An ADF test was performed on the 3-Month MNDR with a null hypothesis of nonstationarity. Table 6 displays the results of the ADF tests for each of the periods. Based on the P-values in Table 6, the MNDRs for the, Early Split, and Late Split periods are found to be nonstationary around their means. Historical MNDRs for those three periods do not help predict future MNDRs. Nonstationarity can be rejected for the MNDR over the Extended period with a P-value below five percent. The Extended MNDR is found to be both not statistically different from zero and stationary around its mean. These findings justify the use of total offset based on the 3-Month MNDR over the Extended period. Table 6 Test for Stationarity (Augmented Dickey-Fuller*) of 3-Month MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) τ-statistic P-Value * A time trend was not included because of the a priori hypothesis of Total Offset. The number of lagged differences included in the ADF test was determined by the Modified Aikaike s Information Criterion with a maximum number of lags set at three. The appendix shows the number of lags used for each test. Final Remarks 12

13 This paper addresses whether the use of the total offset approach is appropriate for FEs. I added to the work of Ewing, Payne, and Piette (2001) by testing MNDRs constructed with the 3- Month and 6-Month Treasury Security and extending the data set to August 2011 for all three MNDRs. Additionally, I took into consideration a study by Sen and Gelles (2006) that found a break-point for the 1-Year Treasury Security in January By regressing MNDRs on a constant and performing ADF tests, the, Extended, Early Split, and Late Split periods were tested to determine whether the MNDR was equal to zero and stationary. The results were mixed and certainly did not provide concrete evidence for either the justification or condemnation of total offset. Despite the lack of uniform results, this study differs from earlier studies in that it shows a sweeping rejection of total offset is no longer warranted. A summary of this study s findings shows the lack of uniform results with regard to total offset. The 1-Year MNDR was found to be not statistically different from zero for the Late Split period but was only stationary for the Extended period. The 6-Month MNDR was not statistically different from zero for the Extended and Early Split periods but was only stationary for the Extended period. Results from the 3-Month MNDR also showed that the Extended and Early Split MNDRs have a constant not statistically different from zero, but only the Extended series exhibited stationarity. Additionally, the 6-Month and 3-Month MNDRs had negative constants in the simple regression over the Late Split period; despite the implication of more than total offset, these Late Split series were found to be nonstationary, implying the historical mean is unsuitable for forecasting by FEs. References 13

14 Ewing, Bradley T., James E. Payne, and Michael J. Piette, The Time Series Behavior of the Medical Cost Net Discount Rate: Implications for Total Offset and Forecasting, Journal of Forensic Economics, 2001, 14(1), Ewing, Bradley T., James E. Payne, and Michael J. Piette, An Inquiry Into the Time Series Properties of Net Discount Rates, Journal of Forensic Economics, 1999, 12(3), Gelles, Gregory M., and Walter D. Johnson, Comment: Justifying Utilization of the Total Offset Method: An Opposing Comment, Journal of Legal Economics, 1996, 6, Ireland, Thomas R., and David Tucek, Historical Net Discount Rates-An Update Through 2010, Journal of Legal Economics, 2011, 18(1), MacKinnon, James G., Numerical Distribution Functions for Unit Root and Cointegration Tests, Journal of Applied Econometrics, 1996, 11(6), Sen, Amit and Gregory Gelles, On the Time Series Properties of the Medical Net Discount Rates, Journal of Business Valuation and Economic Loss Analysis, 2006, 1(1), Article 4. U.S. Department of the Treasury, "Are the CMT Yields Annual Yields?" Resource Center, 12 Mar. 2011, Web, 20 Jan Jones & Laughlin Steel Co. v. Pfeifer, 462 US 523 (1983) 14

15 Total Offset Tests 1-Year Treasury Security Dependent Variable: MNDR_1YR_SIMP Sample: 1981M M05 Included observations: 233 Extension C Dependent Variable: MNDR_1YR_SIMP Sample: 1981M M08 Included observations: 368 C Split: Early Dependent Variable: MNDR_1YR_SIMP Sample: 1981M M01 Included observations: 157 C Split: Late Dependent Variable: MNDR_1YR_SIMP Sample: 1994M M08 Included observations: 211 C

16 6-Month Treasury Security Dependent Variable: MNDR_6MO_COMP Sample: 1981M M05 Included observations: 233 Extension C Dependent Variable: MNDR_6MO_COMP Sample: 1981M M08 Included observations: 368 Split: Early C Dependent Variable: MNDR_6MO_COMP Sample: 1981M M01 Included observations: 157 C Split: Late Dependent Variable: MNDR_6MO_COMP Sample: 1994M M08 Included observations: 211 C Month Treasury Security 16

17 Dependent Variable: MNDR_3_MO_COMP Sample: 1981M M05 Included observations: 233 Extension C Dependent Variable: MNDR_3_MO_COMP Sample: 1981M M08 Included observations: 368 Split: Early C Dependent Variable: MNDR_3_MO_COMP Sample: 1981M M01 Included observations: 157 C Split: Late Dependent Variable: MNDR_3_MO_COMP Date: 01/18/12 Time: 03:06 Sample: 1994M M08 Included observations: 211 C Unit Root Tests (Augmented Dickey-Fuller Test) 17

18 1-Year Treasury Security (No Trend) Null Hypothesis: MNDR_1_YR has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Extension Null Hypothesis: MNDR_1_YR has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Early Null Hypothesis: MNDR_1YR_SIMP has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Late Null Hypothesis: MNDR_1YR_SIMP has a unit root 18

19 Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Month Treasury Security (No Trend) Null Hypothesis: MNDR_6MO_COMP has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Extension Null Hypothesis: MNDR_6MO_COMP has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Early Null Hypothesis: MNDR_6MO_COMP has a unit root 19

20 Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Late Null Hypothesis: MNDR_6MO_COMP has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Month Treasury Security (No Trend) Null Hypothesis: MNDR_3_MO_COMP has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Extension 20

21 Null Hypothesis: MNDR_3_MO_COMP has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Early Null Hypothesis: MNDR_3_MO_COMP has a unit root Exogenous: Constant Lag Length: 2 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Split: Late Null Hypothesis: MNDR_3_MO_COMP has a unit root Exogenous: Constant Lag Length: 3 (Automatic based on Modified AIC, MAXLAG=3) Augmented Dickey-Fuller test statistic Test critical values: 1% level % level % level Year Treasury Security Complex MNDR Total Offset Test 21

22 Table 1A Test for Total Offset of 1-Year MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) Constant T-Statistic P-Value Unit Root Test (Augmented Dickey-Fuller Test) Table 2A Test for Stationarity (Augmented Dickey-Fuller 1 ) of 1-Year MNDR (Jan May 2000) Extended (Jan Aug. 2011) Early Split (Jan Jan.1994) Late Split (Feb Aug. 2011) τ-statistic P-Value A time trend was not included because of the a priori hypothesis of Total Offset. The number of lagged differences included in the ADF test was determined by the Modified Aikaike s Information Criterion with a maximum number of lags set at three. 22

Is the Forward Exchange Rate a Useful Indicator of the Future Exchange Rate?

Is the Forward Exchange Rate a Useful Indicator of the Future Exchange Rate? Is the Forward Exchange Rate a Useful Indicator of the Future Exchange Rate? Emily Polito, Trinity College In the past two decades, there have been many empirical studies both in support of and opposing

More information

Forecasting the US Dollar / Euro Exchange rate Using ARMA Models

Forecasting the US Dollar / Euro Exchange rate Using ARMA Models Forecasting the US Dollar / Euro Exchange rate Using ARMA Models LIUWEI (9906360) - 1 - ABSTRACT...3 1. INTRODUCTION...4 2. DATA ANALYSIS...5 2.1 Stationary estimation...5 2.2 Dickey-Fuller Test...6 3.

More information

ANALYSIS OF EUROPEAN, AMERICAN AND JAPANESE GOVERNMENT BOND YIELDS

ANALYSIS OF EUROPEAN, AMERICAN AND JAPANESE GOVERNMENT BOND YIELDS Applied Time Series Analysis ANALYSIS OF EUROPEAN, AMERICAN AND JAPANESE GOVERNMENT BOND YIELDS Stationarity, cointegration, Granger causality Aleksandra Falkowska and Piotr Lewicki TABLE OF CONTENTS 1.

More information

Chapter 5: Bivariate Cointegration Analysis

Chapter 5: Bivariate Cointegration Analysis Chapter 5: Bivariate Cointegration Analysis 1 Contents: Lehrstuhl für Department Empirische of Wirtschaftsforschung Empirical Research and und Econometrics Ökonometrie V. Bivariate Cointegration Analysis...

More information

Time Series Analysis

Time Series Analysis Time Series Analysis Identifying possible ARIMA models Andrés M. Alonso Carolina García-Martos Universidad Carlos III de Madrid Universidad Politécnica de Madrid June July, 2012 Alonso and García-Martos

More information

Performing Unit Root Tests in EViews. Unit Root Testing

Performing Unit Root Tests in EViews. Unit Root Testing Página 1 de 12 Unit Root Testing The theory behind ARMA estimation is based on stationary time series. A series is said to be (weakly or covariance) stationary if the mean and autocovariances of the series

More information

The information content of lagged equity and bond yields

The information content of lagged equity and bond yields Economics Letters 68 (2000) 179 184 www.elsevier.com/ locate/ econbase The information content of lagged equity and bond yields Richard D.F. Harris *, Rene Sanchez-Valle School of Business and Economics,

More information

Chapter 9: Univariate Time Series Analysis

Chapter 9: Univariate Time Series Analysis Chapter 9: Univariate Time Series Analysis In the last chapter we discussed models with only lags of explanatory variables. These can be misleading if: 1. The dependent variable Y t depends on lags of

More information

Are the US current account deficits really sustainable? National University of Ireland, Galway

Are the US current account deficits really sustainable? National University of Ireland, Galway Provided by the author(s) and NUI Galway in accordance with publisher policies. Please cite the published version when available. Title Are the US current account deficits really sustainable? Author(s)

More information

C(t) (1 + y) 4. t=1. For the 4 year bond considered above, assume that the price today is 900$. The yield to maturity will then be the y that solves

C(t) (1 + y) 4. t=1. For the 4 year bond considered above, assume that the price today is 900$. The yield to maturity will then be the y that solves Economics 7344, Spring 2013 Bent E. Sørensen INTEREST RATE THEORY We will cover fixed income securities. The major categories of long-term fixed income securities are federal government bonds, corporate

More information

Empirical Properties of the Indonesian Rupiah: Testing for Structural Breaks, Unit Roots, and White Noise

Empirical Properties of the Indonesian Rupiah: Testing for Structural Breaks, Unit Roots, and White Noise Volume 24, Number 2, December 1999 Empirical Properties of the Indonesian Rupiah: Testing for Structural Breaks, Unit Roots, and White Noise Reza Yamora Siregar * 1 This paper shows that the real exchange

More information

Cointegration and the ECM

Cointegration and the ECM Cointegration and the ECM Two nonstationary time series are cointegrated if they tend to move together through time. For instance, we have established that the levels of the Fed Funds rate and the 3-year

More information

The relationship between stock market parameters and interbank lending market: an empirical evidence

The relationship between stock market parameters and interbank lending market: an empirical evidence Magomet Yandiev Associate Professor, Department of Economics, Lomonosov Moscow State University mag2097@mail.ru Alexander Pakhalov, PG student, Department of Economics, Lomonosov Moscow State University

More information

The Long-Run Relation Between The Personal Savings Rate And Consumer Sentiment

The Long-Run Relation Between The Personal Savings Rate And Consumer Sentiment The Long-Run Relation Between The Personal Savings Rate And Consumer Sentiment Bradley T. Ewing 1 and James E. Payne 2 This study examined the long run relationship between the personal savings rate and

More information

PITFALLS IN TIME SERIES ANALYSIS. Cliff Hurvich Stern School, NYU

PITFALLS IN TIME SERIES ANALYSIS. Cliff Hurvich Stern School, NYU PITFALLS IN TIME SERIES ANALYSIS Cliff Hurvich Stern School, NYU The t -Test If x 1,..., x n are independent and identically distributed with mean 0, and n is not too small, then t = x 0 s n has a standard

More information

Econometrics I: Econometric Methods

Econometrics I: Econometric Methods Econometrics I: Econometric Methods Jürgen Meinecke Research School of Economics, Australian National University 24 May, 2016 Housekeeping Assignment 2 is now history The ps tute this week will go through

More information

DEPARTMENT OF ECONOMICS CREDITOR PROTECTION AND BANKING SYSTEM DEVELOPMENT IN INDIA

DEPARTMENT OF ECONOMICS CREDITOR PROTECTION AND BANKING SYSTEM DEVELOPMENT IN INDIA DEPARTMENT OF ECONOMICS CREDITOR PROTECTION AND BANKING SYSTEM DEVELOPMENT IN INDIA Simon Deakin, University of Cambridge, UK Panicos Demetriades, University of Leicester, UK Gregory James, University

More information

Business Cycles and Natural Gas Prices

Business Cycles and Natural Gas Prices Department of Economics Discussion Paper 2004-19 Business Cycles and Natural Gas Prices Apostolos Serletis Department of Economics University of Calgary Canada and Asghar Shahmoradi Department of Economics

More information

The Impact of Public Infrastructure on Private Investment in the US

The Impact of Public Infrastructure on Private Investment in the US The Impact of Public Infrastructure on Private Investment in the US Ben Miller Advisor: Mahmud Yesuf University Honors in Mathematics and Economics 1 Abstract Economists and politicians are concerned with

More information

Relationship among crude oil prices, share prices and exchange rates

Relationship among crude oil prices, share prices and exchange rates Relationship among crude oil prices, share prices and exchange rates Do higher share prices and weaker dollar lead to higher crude oil prices? Akira YANAGISAWA Leader Energy Demand, Supply and Forecast

More information

Table 1: Unit Root Tests KPSS Test Augmented Dickey-Fuller Test with Time Trend

Table 1: Unit Root Tests KPSS Test Augmented Dickey-Fuller Test with Time Trend Table 1: Unit Root Tests KPSS Test Augmented Dickey-Fuller Test with Time Trend with Time Trend test statistic p-value test statistic Corn -2.953.146.179 Soy -2.663.252.353 Corn -2.752.215.171 Soy -2.588.285.32

More information

Unit root properties of natural gas spot and futures prices: The relevance of heteroskedasticity in high frequency data

Unit root properties of natural gas spot and futures prices: The relevance of heteroskedasticity in high frequency data DEPARTMENT OF ECONOMICS ISSN 1441-5429 DISCUSSION PAPER 20/14 Unit root properties of natural gas spot and futures prices: The relevance of heteroskedasticity in high frequency data Vinod Mishra and Russell

More information

Testing for Granger causality between stock prices and economic growth

Testing for Granger causality between stock prices and economic growth MPRA Munich Personal RePEc Archive Testing for Granger causality between stock prices and economic growth Pasquale Foresti 2006 Online at http://mpra.ub.uni-muenchen.de/2962/ MPRA Paper No. 2962, posted

More information

Stock market booms and real economic activity: Is this time different?

Stock market booms and real economic activity: Is this time different? International Review of Economics and Finance 9 (2000) 387 415 Stock market booms and real economic activity: Is this time different? Mathias Binswanger* Institute for Economics and the Environment, University

More information

Powerful new tools for time series analysis

Powerful new tools for time series analysis Christopher F Baum Boston College & DIW August 2007 hristopher F Baum ( Boston College & DIW) NASUG2007 1 / 26 Introduction This presentation discusses two recent developments in time series analysis by

More information

RELATIONSHIP BETWEEN STOCK MARKET VOLATILITY AND EXCHANGE RATE: A STUDY OF KSE

RELATIONSHIP BETWEEN STOCK MARKET VOLATILITY AND EXCHANGE RATE: A STUDY OF KSE RELATIONSHIP BETWEEN STOCK MARKET VOLATILITY AND EXCHANGE RATE: A STUDY OF KSE Waseem ASLAM Department of Finance and Economics, Foundation University Rawalpindi, Pakistan seem_aslam@yahoo.com Abstract:

More information

Econ 330 Exam 1 Name ID Section Number

Econ 330 Exam 1 Name ID Section Number Econ 330 Exam 1 Name ID Section Number MULTIPLE CHOICE. Choose the one alternative that best completes the statement or answers the question. 1) If during the past decade the average rate of monetary growth

More information

Price volatility in the silver spot market: An empirical study using Garch applications

Price volatility in the silver spot market: An empirical study using Garch applications Price volatility in the silver spot market: An empirical study using Garch applications ABSTRACT Alan Harper, South University Zhenhu Jin Valparaiso University Raufu Sokunle UBS Investment Bank Manish

More information

The VAR models discussed so fare are appropriate for modeling I(0) data, like asset returns or growth rates of macroeconomic time series.

The VAR models discussed so fare are appropriate for modeling I(0) data, like asset returns or growth rates of macroeconomic time series. Cointegration The VAR models discussed so fare are appropriate for modeling I(0) data, like asset returns or growth rates of macroeconomic time series. Economic theory, however, often implies equilibrium

More information

THE U.S. CURRENT ACCOUNT: THE IMPACT OF HOUSEHOLD WEALTH

THE U.S. CURRENT ACCOUNT: THE IMPACT OF HOUSEHOLD WEALTH THE U.S. CURRENT ACCOUNT: THE IMPACT OF HOUSEHOLD WEALTH Grant Keener, Sam Houston State University M.H. Tuttle, Sam Houston State University 21 ABSTRACT Household wealth is shown to have a substantial

More information

David G. Tucek Value Economics, LLC 13024 Vinson Court St. Louis, MO 63043 Tel: 314/434 8633 Cell: 314/440 4925 David.Tucek@valueeconomics.

David G. Tucek Value Economics, LLC 13024 Vinson Court St. Louis, MO 63043 Tel: 314/434 8633 Cell: 314/440 4925 David.Tucek@valueeconomics. 1 Economic Controversy in Personal Injury Cases An Example of a Bad Example Submitted for Publication in the Journal of the Missouri Bar, (Draft 2/14/2012) David G. Tucek Value Economics, LLC 13024 Vinson

More information

FORECASTING DEPOSIT GROWTH: Forecasting BIF and SAIF Assessable and Insured Deposits

FORECASTING DEPOSIT GROWTH: Forecasting BIF and SAIF Assessable and Insured Deposits Technical Paper Series Congressional Budget Office Washington, DC FORECASTING DEPOSIT GROWTH: Forecasting BIF and SAIF Assessable and Insured Deposits Albert D. Metz Microeconomic and Financial Studies

More information

Examining the Relationship between ETFS and Their Underlying Assets in Indian Capital Market

Examining the Relationship between ETFS and Their Underlying Assets in Indian Capital Market 2012 2nd International Conference on Computer and Software Modeling (ICCSM 2012) IPCSIT vol. 54 (2012) (2012) IACSIT Press, Singapore DOI: 10.7763/IPCSIT.2012.V54.20 Examining the Relationship between

More information

Macroeconomic Variables and the Demand for Life Insurance in Malaysia. Chee Chee Lim Steven Haberman

Macroeconomic Variables and the Demand for Life Insurance in Malaysia. Chee Chee Lim Steven Haberman Macroeconomic Variables and the Demand for Life Insurance in Malaysia ABSTRACT Chee Chee Lim Steven Haberman Faculty of Actuarial Science and Statistics, CASS Business School, City University (London)

More information

Business cycles and natural gas prices

Business cycles and natural gas prices Business cycles and natural gas prices Apostolos Serletis and Asghar Shahmoradi Abstract This paper investigates the basic stylised facts of natural gas price movements using data for the period that natural

More information

Minimum LM Unit Root Test with One Structural Break. Junsoo Lee Department of Economics University of Alabama

Minimum LM Unit Root Test with One Structural Break. Junsoo Lee Department of Economics University of Alabama Minimum LM Unit Root Test with One Structural Break Junsoo Lee Department of Economics University of Alabama Mark C. Strazicich Department of Economics Appalachian State University December 16, 2004 Abstract

More information

Co-integration, Causality, Money and Income in India

Co-integration, Causality, Money and Income in India Co-integration, Causality, Money and Income in India Inder Sekhar Yadav Abstract This paper investigates empirically the existence of a long-run relationship between money supply (MS) and national income

More information

Non-Stationary Time Series andunitroottests

Non-Stationary Time Series andunitroottests Econometrics 2 Fall 2005 Non-Stationary Time Series andunitroottests Heino Bohn Nielsen 1of25 Introduction Many economic time series are trending. Important to distinguish between two important cases:

More information

Econ 371 Exam #4 - Practice

Econ 371 Exam #4 - Practice Econ 37 Exam #4 - Practice Multiple Choice (5 points each): For each of the following, select the single most appropriate option to complete the statement. ) The following will not cause correlation between

More information

Nonlinearity and stationarity of inflation rates:

Nonlinearity and stationarity of inflation rates: THE UNIVERSITY OF TEXAS AT SAN ANTONIO, COLLEGE OF BUSINESS Working Paper SERIES Date February 23, 2010 WP # 0006ECO-106-2010 Nonlinearity and stationarity of inflation rates: Evidence from the euro-zone

More information

Dynamic Relationship between Interest Rate and Stock Price: Empirical Evidence from Colombo Stock Exchange

Dynamic Relationship between Interest Rate and Stock Price: Empirical Evidence from Colombo Stock Exchange International Journal of Business and Social Science Vol. 6, No. 4; April 2015 Dynamic Relationship between Interest Rate and Stock Price: Empirical Evidence from Colombo Stock Exchange AAMD Amarasinghe

More information

Term Structure of Interest Rates

Term Structure of Interest Rates Appendix 8B Term Structure of Interest Rates To explain the process of estimating the impact of an unexpected shock in short-term interest rates on the entire term structure of interest rates, FIs use

More information

Department of Economics

Department of Economics Department of Economics Working Paper Do Stock Market Risk Premium Respond to Consumer Confidence? By Abdur Chowdhury Working Paper 2011 06 College of Business Administration Do Stock Market Risk Premium

More information

Chapter 12: Time Series Models

Chapter 12: Time Series Models Chapter 12: Time Series Models In this chapter: 1. Estimating ad hoc distributed lag & Koyck distributed lag models (UE 12.1.3) 2. Testing for serial correlation in Koyck distributed lag models (UE 12.2.2)

More information

GRADO EN ECONOMÍA. Is the Forward Rate a True Unbiased Predictor of the Future Spot Exchange Rate?

GRADO EN ECONOMÍA. Is the Forward Rate a True Unbiased Predictor of the Future Spot Exchange Rate? FACULTAD DE CIENCIAS ECONÓMICAS Y EMPRESARIALES GRADO EN ECONOMÍA Is the Forward Rate a True Unbiased Predictor of the Future Spot Exchange Rate? Autor: Elena Renedo Sánchez Tutor: Juan Ángel Jiménez Martín

More information

AN EMPIRICAL INVESTIGATION OF THE RELATIONSHIP AMONG P/E RATIO, STOCK RETURN AND DIVIDEND YIELS FOR ISTANBUL STOCK EXCHANGE

AN EMPIRICAL INVESTIGATION OF THE RELATIONSHIP AMONG P/E RATIO, STOCK RETURN AND DIVIDEND YIELS FOR ISTANBUL STOCK EXCHANGE AN EMPIRICAL INVESTIGATION OF THE RELATIONSHIP AMONG P/E RATIO, STOCK RETURN AND DIVIDEND YIELS FOR ISTANBUL STOCK EXCHANGE Funda H. SEZGIN Mimar Sinan Fine Arts University, Faculty of Science and Letters

More information

EXPORT INSTABILITY, INVESTMENT AND ECONOMIC GROWTH IN ASIAN COUNTRIES: A TIME SERIES ANALYSIS

EXPORT INSTABILITY, INVESTMENT AND ECONOMIC GROWTH IN ASIAN COUNTRIES: A TIME SERIES ANALYSIS ECONOMIC GROWTH CENTER YALE UNIVERSITY P.O. Box 208269 27 Hillhouse Avenue New Haven, Connecticut 06520-8269 CENTER DISCUSSION PAPER NO. 799 EXPORT INSTABILITY, INVESTMENT AND ECONOMIC GROWTH IN ASIAN

More information

ANALYSIS OF THE EFFECTS OF PRE ANNOUNCEMENT OF S&P 500 INDEX CHANGES Stoyu I. Ivanov, San Jose State University

ANALYSIS OF THE EFFECTS OF PRE ANNOUNCEMENT OF S&P 500 INDEX CHANGES Stoyu I. Ivanov, San Jose State University The International Journal of Business and Finance Research VOLUME 7 NUMBER 5 23 ANALYSIS OF THE EFFECTS OF PRE ANNOUNCEMENT OF S&P 5 INDEX CHANGES Stoyu I. Ivanov, San Jose State University ABSTRACT In

More information

Bonds and Yield to Maturity

Bonds and Yield to Maturity Bonds and Yield to Maturity Bonds A bond is a debt instrument requiring the issuer to repay to the lender/investor the amount borrowed (par or face value) plus interest over a specified period of time.

More information

Cointegration and error correction

Cointegration and error correction EVIEWS tutorial: Cointegration and error correction Professor Roy Batchelor City University Business School, London & ESCP, Paris EVIEWS Tutorial 1 EVIEWS On the City University system, EVIEWS 3.1 is in

More information

Pricing Corn Calendar Spread Options. Juheon Seok and B. Wade Brorsen

Pricing Corn Calendar Spread Options. Juheon Seok and B. Wade Brorsen Pricing Corn Calendar Spread Options by Juheon Seok and B. Wade Brorsen Suggested citation format: Seok, J., and B. W. Brorsen. 215. Pricing Corn Calendar Spread Options. Proceedings of the NCCC-134 Conference

More information

Estimating Risk free Rates. Aswath Damodaran. Stern School of Business. 44 West Fourth Street. New York, NY 10012. Adamodar@stern.nyu.

Estimating Risk free Rates. Aswath Damodaran. Stern School of Business. 44 West Fourth Street. New York, NY 10012. Adamodar@stern.nyu. Estimating Risk free Rates Aswath Damodaran Stern School of Business 44 West Fourth Street New York, NY 10012 Adamodar@stern.nyu.edu Estimating Risk free Rates Models of risk and return in finance start

More information

Practice Set and Solutions #2

Practice Set and Solutions #2 723G26/2012-10-10 Practice Set and Solutions #2 What to do with this practice set? Practice sets are handed out to help students master the material of the course and prepare for the final exam. These

More information

A Primer on Forecasting Business Performance

A Primer on Forecasting Business Performance A Primer on Forecasting Business Performance There are two common approaches to forecasting: qualitative and quantitative. Qualitative forecasting methods are important when historical data is not available.

More information

Bond valuation. Present value of a bond = present value of interest payments + present value of maturity value

Bond valuation. Present value of a bond = present value of interest payments + present value of maturity value Bond valuation A reading prepared by Pamela Peterson Drake O U T L I N E 1. Valuation of long-term debt securities 2. Issues 3. Summary 1. Valuation of long-term debt securities Debt securities are obligations

More information

CREATING A CORPORATE BOND SPOT YIELD CURVE FOR PENSION DISCOUNTING DEPARTMENT OF THE TREASURY OFFICE OF ECONOMIC POLICY WHITE PAPER FEBRUARY 7, 2005

CREATING A CORPORATE BOND SPOT YIELD CURVE FOR PENSION DISCOUNTING DEPARTMENT OF THE TREASURY OFFICE OF ECONOMIC POLICY WHITE PAPER FEBRUARY 7, 2005 CREATING A CORPORATE BOND SPOT YIELD CURVE FOR PENSION DISCOUNTING I. Introduction DEPARTMENT OF THE TREASURY OFFICE OF ECONOMIC POLICY WHITE PAPER FEBRUARY 7, 2005 Plan sponsors, plan participants and

More information

Algorithmic Trading Session 6 Trade Signal Generation IV Momentum Strategies. Oliver Steinki, CFA, FRM

Algorithmic Trading Session 6 Trade Signal Generation IV Momentum Strategies. Oliver Steinki, CFA, FRM Algorithmic Trading Session 6 Trade Signal Generation IV Momentum Strategies Oliver Steinki, CFA, FRM Outline Introduction What is Momentum? Tests to Discover Momentum Interday Momentum Strategies Intraday

More information

Do Heating Oil Prices Adjust Asymmetrically To Changes In Crude Oil Prices Paul Berhanu Girma, State University of New York at New Paltz, USA

Do Heating Oil Prices Adjust Asymmetrically To Changes In Crude Oil Prices Paul Berhanu Girma, State University of New York at New Paltz, USA Do Heating Oil Prices Adjust Asymmetrically To Changes In Crude Oil Prices Paul Berhanu Girma, State University of New York at New Paltz, USA ABSTRACT This study investigated if there is an asymmetric

More information

Do Global Oil Price Changes Affect Indian Stock Market Returns?

Do Global Oil Price Changes Affect Indian Stock Market Returns? Journal of Management & Public Policy Vol. 6, No. 2, June 2015, Pp. 29-41 ISSN: 0976-0148 Do Global Oil Price Changes Affect Indian Stock Market Returns? Saif Siddiqui Centre of Management Studies, Jamia

More information

The link between unemployment and inflation using Johansen s. co-integration approach and vector error correction modelling.

The link between unemployment and inflation using Johansen s. co-integration approach and vector error correction modelling. Proceedings 59th ISI World Statistics Congress, 25-30 August 2013, Hong Kong (Session CPS102) p.4340 The link between unemployment and inflation using Johansen s co-integration approach and vector error

More information

Relationship between Commodity Prices and Exchange Rate in Light of Global Financial Crisis: Evidence from Australia

Relationship between Commodity Prices and Exchange Rate in Light of Global Financial Crisis: Evidence from Australia Relationship between Commodity Prices and Exchange Rate in Light of Global Financial Crisis: Evidence from Australia Omar K. M. R. Bashar and Sarkar Humayun Kabir Abstract This study seeks to identify

More information

Pricing and Strategy for Muni BMA Swaps

Pricing and Strategy for Muni BMA Swaps J.P. Morgan Management Municipal Strategy Note BMA Basis Swaps: Can be used to trade the relative value of Libor against short maturity tax exempt bonds. Imply future tax rates and can be used to take

More information

Division of Economics A.J. Palumbo School of Business Administration and McAnulty College of Liberal Arts Duquesne University Pittsburgh, Pennsylvania

Division of Economics A.J. Palumbo School of Business Administration and McAnulty College of Liberal Arts Duquesne University Pittsburgh, Pennsylvania Division of Economics A.J. Palumbo School of Business Administration and McAnulty College of Liberal Arts Duquesne University Pittsburgh, Pennsylvania COMPARING THE ACCURACY FOR SIX METHODS OF CALCULATING

More information

Empirical Analysis of Housing Prices in Chinese Market

Empirical Analysis of Housing Prices in Chinese Market International Journal of Trade, Economics and Finance, Vol., No. 5, October 2012 Empirical Analysis of Housing Prices in Chinese Market Jieqiong Wang and Dejun Xie Abstract This work constitutes, in part,

More information

Comments on Gali s Hysteresis and the European Unemployment Problem Revised

Comments on Gali s Hysteresis and the European Unemployment Problem Revised Comments on Gali s Hysteresis and the European Unemployment Problem Revised Robert J. Gordon Northwestern University, NBER, CEPR ECB Forum on Central Banking, Sintra, Portugal, May 22, 2015 Starting Point:

More information

THE EFFECTS OF BANKING CREDIT ON THE HOUSE PRICE

THE EFFECTS OF BANKING CREDIT ON THE HOUSE PRICE THE EFFECTS OF BANKING CREDIT ON THE HOUSE PRICE * Adibeh Savari 1, Yaser Borvayeh 2 1 MA Student, Department of Economics, Science and Research Branch, Islamic Azad University, Khuzestan, Iran 2 MA Student,

More information

Temi di discussione. del Servizio Studi. Stock market fluctuations and money demand in Italy, 1913-2003. by Massimo Caruso

Temi di discussione. del Servizio Studi. Stock market fluctuations and money demand in Italy, 1913-2003. by Massimo Caruso Temi di discussione del Servizio Studi Stock market fluctuations and money demand in Italy, 1913-2003 by Massimo Caruso Number 576 - February 2006 The purpose of the Temi di discussione series is to promote

More information

A Discussion on Discount Rates in Alberta

A Discussion on Discount Rates in Alberta A Discussion on Discount Rates in Alberta In personal injury cases, a lump sum award often is provided to a plaintiff as compensation for the loss of a future stream of employment earnings, or to compensate

More information

AFM 271 Practice Problem Set #1 Spring 2005

AFM 271 Practice Problem Set #1 Spring 2005 AFM 271 Practice Problem Set #1 Spring 2005 1. Text problems: Chapter 1 1, 3, 4 Chapter 2 5 Chapter 3 2, 6, 7 Chapter 4 2, 6, 12, 14, 16, 18, 20, 22, 24, 26, 30, 32, 34, 38, 40, 46, 48 Chapter 5 2, 4,

More information

Impact of Fiscal Variables on Economic Development of Pakistan

Impact of Fiscal Variables on Economic Development of Pakistan Romanian Journal of Fiscal Policy Volume 2, Issue 2, July - December 2011, Pages 1-10 Impact of Fiscal Variables on Economic Development of Pakistan Zaheer Khan KAKAR Department Of Economics, National

More information

FDI and Economic Growth Relationship: An Empirical Study on Malaysia

FDI and Economic Growth Relationship: An Empirical Study on Malaysia International Business Research April, 2008 FDI and Economic Growth Relationship: An Empirical Study on Malaysia Har Wai Mun Faculty of Accountancy and Management Universiti Tunku Abdul Rahman Bander Sungai

More information

Annual Treasury And Investment Portfolio Update for 2015

Annual Treasury And Investment Portfolio Update for 2015 Item No.: 7d_Supp Meeting Date: March 8, 2016 Annual Treasury And Investment Portfolio Update for 2015 Commission Briefing Presented by Diane Campbell March 8, 2016 Treasury Management Update Background

More information

Vector Time Series Model Representations and Analysis with XploRe

Vector Time Series Model Representations and Analysis with XploRe 0-1 Vector Time Series Model Representations and Analysis with plore Julius Mungo CASE - Center for Applied Statistics and Economics Humboldt-Universität zu Berlin mungo@wiwi.hu-berlin.de plore MulTi Motivation

More information

Present Value and the Uncertain Future

Present Value and the Uncertain Future Present Value and the Uncertain Future BAMSL Seminar St. Louis, Missouri Friday April 22, 2011 Scott Gilbert, Ph.D. Economist & Professor Southern Illinois University Carbondale gilberts@siu.edu (618)

More information

The Relationship between Current Account and Government Budget Balance: The Case of Kuwait

The Relationship between Current Account and Government Budget Balance: The Case of Kuwait International Journal of Humanities and Social Science Vol. 2 No. 7; April 2012 The Relationship between Current Account and Government Budget Balance: The Case of Kuwait Abstract Ebrahim Merza Economics

More information

The US Municipal Bond Risk Model. Oren Cheyette

The US Municipal Bond Risk Model. Oren Cheyette The US Municipal Bond Risk Model Oren Cheyette THE US MUNICIPAL BOND RISK MODEL Overview Barra s integrated risk model includes coverage of municipal bonds accounting for marketwide and issuer-specific

More information

A Trading Strategy Based on the Lead-Lag Relationship of Spot and Futures Prices of the S&P 500

A Trading Strategy Based on the Lead-Lag Relationship of Spot and Futures Prices of the S&P 500 A Trading Strategy Based on the Lead-Lag Relationship of Spot and Futures Prices of the S&P 500 FE8827 Quantitative Trading Strategies 2010/11 Mini-Term 5 Nanyang Technological University Submitted By:

More information

CHAPTER 16: MANAGING BOND PORTFOLIOS

CHAPTER 16: MANAGING BOND PORTFOLIOS CHAPTER 16: MANAGING BOND PORTFOLIOS PROBLEM SETS 1. While it is true that short-term rates are more volatile than long-term rates, the longer duration of the longer-term bonds makes their prices and their

More information

Unit roots in macroeconomic time series:

Unit roots in macroeconomic time series: Unit roots in macroeconomic time series: theory, implications, and evidence Gilberto A. Libanio Assistant Professor at Federal University of Minas Gerais (Brazil) and Doctoral Candidate in Economics at

More information

APPENDIX C REPORT TO JUDGE PRESSLER RE PREJUDGMENT INTEREST Prejudgment Interest Should Not Be Allowed for Future Lost Wages or Future Medical Expenses The Supreme Court asked the Civil Practice

More information

Performance of pairs trading on the S&P 500 index

Performance of pairs trading on the S&P 500 index Performance of pairs trading on the S&P 500 index By: Emiel Verhaert, studentnr: 348122 Supervisor: Dick van Dijk Abstract Until now, nearly all papers focused on pairs trading have just implemented the

More information

P/E Changes: Some New Results

P/E Changes: Some New Results University of Nebraska - Lincoln DigitalCommons@University of Nebraska - Lincoln Finance Department Faculty Publications Finance Department 1-1-2009 P/E Changes: Some New Results Thomas S. Zorn University

More information

On the long run relationship between gold and silver prices A note

On the long run relationship between gold and silver prices A note Global Finance Journal 12 (2001) 299 303 On the long run relationship between gold and silver prices A note C. Ciner* Northeastern University College of Business Administration, Boston, MA 02115-5000,

More information

THE IMPACT OF EXCHANGE RATE VOLATILITY ON BRAZILIAN MANUFACTURED EXPORTS

THE IMPACT OF EXCHANGE RATE VOLATILITY ON BRAZILIAN MANUFACTURED EXPORTS THE IMPACT OF EXCHANGE RATE VOLATILITY ON BRAZILIAN MANUFACTURED EXPORTS ANTONIO AGUIRRE UFMG / Department of Economics CEPE (Centre for Research in International Economics) Rua Curitiba, 832 Belo Horizonte

More information

TIME SERIES ANALYSIS OF CHINA S EXTERNAL DEBT COMPONENTS, FOREIGN EXCHANGE RESERVES AND ECONOMIC GROWTH RATES. Hüseyin Çetin

TIME SERIES ANALYSIS OF CHINA S EXTERNAL DEBT COMPONENTS, FOREIGN EXCHANGE RESERVES AND ECONOMIC GROWTH RATES. Hüseyin Çetin TIME SERIES ANALYSIS OF CHINA S EXTERNAL DEBT COMPONENTS, FOREIGN EXCHANGE RESERVES AND ECONOMIC GROWTH RATES Hüseyin Çetin Phd Business Administration Candidate Okan University Social Science Institute,

More information

A Basic Introduction to the Methodology Used to Determine a Discount Rate

A Basic Introduction to the Methodology Used to Determine a Discount Rate A Basic Introduction to the Methodology Used to Determine a Discount Rate By Dubravka Tosic, Ph.D. The term discount rate is one of the most fundamental, widely used terms in finance and economics. Whether

More information

Volatility in the Overnight Money-Market Rate

Volatility in the Overnight Money-Market Rate 5 Volatility in the Overnight Money-Market Rate Allan Bødskov Andersen, Economics INTRODUCTION AND SUMMARY This article analyses the day-to-day fluctuations in the Danish overnight money-market rate during

More information

Stock Returns and Equity Premium Evidence Using Dividend Price Ratios and Dividend Yields in Malaysia

Stock Returns and Equity Premium Evidence Using Dividend Price Ratios and Dividend Yields in Malaysia Stock Returns and Equity Premium Evidence Using Dividend Price Ratios and Dividend Yields in Malaysia By David E. Allen 1 and Imbarine Bujang 1 1 School of Accounting, Finance and Economics, Edith Cowan

More information

Converting From A Present Value Lump Sum To A Future Payment Stream. Michael L. Brookshire and Thomas R. Ireland* I. Introduction

Converting From A Present Value Lump Sum To A Future Payment Stream. Michael L. Brookshire and Thomas R. Ireland* I. Introduction Journal of Forensic Economics 7(2), 1994, pp. 151--157 1994 by the National Association of Forensm Economics Converting From A Present Value Lump Sum To A Future Payment Stream Michael L. Brookshire and

More information

Forensic & Valuation Services Practice Aid Discount Rates, Risk, and Uncertainty in Economic Damages Calculations

Forensic & Valuation Services Practice Aid Discount Rates, Risk, and Uncertainty in Economic Damages Calculations Forensic & Valuation Services Practice Aid Discount Rates, Risk, and Uncertainty in Economic Damages Calculations Page 1 Copyright 2013 by American Institute of Certified Public Accountants, Inc. New York,

More information

Chapter Nine Selected Solutions

Chapter Nine Selected Solutions Chapter Nine Selected Solutions 1. What is the difference between book value accounting and market value accounting? How do interest rate changes affect the value of bank assets and liabilities under the

More information

Journal of International Money and Finance

Journal of International Money and Finance Journal of International Money and Finance 30 (2011) 246 267 Contents lists available at ScienceDirect Journal of International Money and Finance journal homepage: www.elsevier.com/locate/jimf Why panel

More information

LO.a: Interpret interest rates as required rates of return, discount rates, or opportunity costs.

LO.a: Interpret interest rates as required rates of return, discount rates, or opportunity costs. LO.a: Interpret interest rates as required rates of return, discount rates, or opportunity costs. 1. The minimum rate of return that an investor must receive in order to invest in a project is most likely

More information

Equity Risk Premium Article Michael Annin, CFA and Dominic Falaschetti, CFA

Equity Risk Premium Article Michael Annin, CFA and Dominic Falaschetti, CFA Equity Risk Premium Article Michael Annin, CFA and Dominic Falaschetti, CFA This article appears in the January/February 1998 issue of Valuation Strategies. Executive Summary This article explores one

More information

EXCHANGE RATE PASS-THROUGH TO INFLATION IN MONGOLIA

EXCHANGE RATE PASS-THROUGH TO INFLATION IN MONGOLIA 1 EXCHANGE RATE PASS-THROUGH TO INFLATION IN MONGOLIA by Gan-Ochir Doojav doojav_ganochir@mongolbank.mn February 2009 Economist at the Monetary Policy and Research Department of the Bank of Mongolia. Opinions

More information

The average hotel manager recognizes the criticality of forecasting. However, most

The average hotel manager recognizes the criticality of forecasting. However, most Introduction The average hotel manager recognizes the criticality of forecasting. However, most managers are either frustrated by complex models researchers constructed or appalled by the amount of time

More information

S&P Year Rolling Period Total Returns

S&P Year Rolling Period Total Returns S&P 500 10 Year Rolling Period Total Returns Summary: 1926 June 2013 700% 600% 500% 400% 300% 200% 100% 0% 100% Scatter chart of all 931 ten year periods. There were 931 ten year rolling periods from January

More information

Wharton Financial Institutions Center Policy Brief: Personal Finance. Measuring the Tax Benefit of a Tax-Deferred Annuity

Wharton Financial Institutions Center Policy Brief: Personal Finance. Measuring the Tax Benefit of a Tax-Deferred Annuity Wharton Financial Institutions Center Policy Brief: Personal Finance Measuring the Tax Benefit of a Tax-Deferred Annuity David F. Babbel* Fellow, Wharton Financial Institutions Center babbel@wharton.upenn.edu

More information

Underwriting Cycles in German Property-Liability Insurance

Underwriting Cycles in German Property-Liability Insurance Underwriting Cycles in German Property-Liability Insurance Martin Eling und Michael Luhnen Preprint Series: 2009-06 Fakultät für Mathematik und Wirtschaftswissenschaften UNIVERSITÄT ULM Underwriting Cycles

More information

Causality between Government Expenditure and National Income: Evidence from Sudan. Ebaidalla Mahjoub Ebaidalla 1

Causality between Government Expenditure and National Income: Evidence from Sudan. Ebaidalla Mahjoub Ebaidalla 1 Journal of Economic Cooperation and Development, 34, 4 (2013), 61-76 Causality between Government Expenditure and National Income: Evidence from Sudan Ebaidalla Mahjoub Ebaidalla 1 This study aims to determine

More information