TAILIEUCHUNG - TAX AND LIQUIDITY EFFECTS IN PRICING GOVERNMENT BONDS

As is common in the region, India is a bank-dominated market (Figure 3), and the relative importance of bank assets as a percentage of GDP has continued to grow—partly as banking penetration has deepened with financial liberalization, and partly as a result of the ongoing need for deficit financing. However, the ratio of bank assets to GDP is still low by comparison with other emerging East Asian economies, indicating that India still has some way to go before its banking sector is fully developed. The same pattern is also seen in the People’s Republic of China (PRC), which like. | THE JOURNAL OF FINANCE VOL. LIII NO. 5 OCTOBER 1998 Tax and Liquidity Effects in Pricing Government Bonds EDWIN J. ELTON and T. CLIFTON GREEN ABSTRACT Daily data from interdealer government bond brokers are examined for tax and liquidity effects. We use two approaches to create cash flow matching portfolios of similar securities and look for pricing discrepancies associated with liquidity or tax effects. We also look for the presence of tax and liquidity effects by including a liquidity term when f itting a cubic spline to the after-tax yield curve. We find evidence of tax timing options and liquidity effects. However the effects are much smaller than previously reported and the effects of liquidity are primarily due to high volume bonds with long maturities. Cash flows of non-callable Treasury securities are fixed and certain simplifying the pricing of these assets to a present value calculation using the current term structure of interest rates. It is well known however that pric ing errors exist when government securities are priced by discounting the cash f lows by any set of estimated spot rates even for non-f lower bonds without option features. A number of theories have been offered to explain these pricing discrepancies. Explanations include economic inf luences such as liquidity effects tax regime effects tax clienteles tax timing options and the use of bonds in the overnight repurchase market. Another potential source of pricing errors is data problems that arise from nonsynchronous trading and the fact that the prices found in common data sets may be estimates from a model or the best guess of a trader. It is diff icult to distinguish between these various explanations because securities rarely exist that are affected by only one of the effects. For example illiquid securities are likely to be associated with pricing errors due to nonsynchronous trading and may also have coupons that would lead to considerable tax effects. In addition it is difficult to

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