Monthly Archives: May 2014

ASSET HOLDING AND CONSUMPTION VOLATILITY: Evidence on asset returns and asset ownership in the UK 3

Posted by Kathryn Schwartz on May 30, 2014
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Given the large changes in the level of ownership of shares and the differences across cohorts, it might be expected that the composition of the group of shareholders has changed over the period. In general, shareholders tend to be older and better educated than the rest of the population, but these differences have been getting smaller over time (as the results of the probit regression of share ownership in the next section will show more clearly).

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ASSET HOLDING AND CONSUMPTION VOLATILITY: Evidence on asset returns and asset ownership in the UK 2

Posted by Kathryn Schwartz on May 28, 2014
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The rapid increase in share ownership coincided with a number of measures designed by the Conservative Government to promote a cshare-owning democracy’. The first was a program of privatization and the heavily advertised flotation of a number of public utilities including British Telecom (1984) and British Gas (1986). Privatisation accounts for a large part of the increase in the number of shareowners. More detailed information on share ownership contained in the 1987 and 1988 General Household Surveys, for example, shows that more than half of all shareholders owned shares in privatized companies, and that a large proportion owned shares only in a privatized company. However, the evidence also suggests that there was a more general increase in ownership of shares.
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ASSET HOLDING AND CONSUMPTION VOLATILITY: Evidence on asset returns and asset ownership in the UK

Posted by Kathryn Schwartz on May 26, 2014
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Patterns of share ownership in the UK
In keeping with the US, the overwhelming majority of UK households – more than 75 per cent – do not own shares direcdy. Given the substantial excess returns to shares (see Table 1), this is a puzzle (see Haliassos and Bertault, 1995, for a discussion of possible explanations). Furthermore, levels of share ownership greater than 20 per cent are a recent phenomenon.
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ASSET HOLDING AND CONSUMPTION VOLATILITY: The Consumption CAPM model 3

Posted by Kathryn Schwartz on May 24, 2014
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In the absence of measurement error, and under the assumption of rational expectations, any variable dated t-1 or earlier is a valid instrument Considering equations (5) and (6) for two different assets, j and iy we can obtain a log-linear version of equation (4). After some manipulation, it is possible to derive: Source
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ASSET HOLDING AND CONSUMPTION VOLATILITY: The Consumption CAPM model 2

Posted by Kathryn Schwartz on May 22, 2014
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A kev implication of Consumption CAPM models, therefore, is that equilibrium returns are determined by a single factor: the IMRS. If there are complete markets and common informatioasets across all consumers, observed asset returns are sufficient to identify the IMRS. When either of these assumptions is violated one can derive relationships, implied by the observed asset returns, that impose restrictions on the unconditional moments of the IMRS. Hansen and Jagannathan (1991) derive bounds on the mean and variance of the benchmark portfolio from observed data on asset returns.
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ASSET HOLDING AND CONSUMPTION VOLATILITY: The Consumption CAPM model

Posted by Kathryn Schwartz on May 20, 2014
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Consider the standard intertemporal optimization problem facing a generic consumer with access to N different assets. Consumption and portfolio decisions are assumed to follow from the maximization of the expected lifetime value of utility from consumption (appropriately discounted) subject to an intertemporal budget constraint that reflects the intertemporal allocation possibilities available. Assuming that lifetime utility displays additive separability (and omitting individual indexes for simplicity) the maximization problem can be written as follows: Source
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where Cs denotes (non durable) consumption in period j, v denotes other factors that might affect the (marginal) utility of non durable consumption such as demographic variables, /3 is the discount factor, Ak is the amount of wealth held in asset к and / is the rate of return on that asset.
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ASSET HOLDING AND CONSUMPTION VOLATILITY: Introduction 3

Posted by Kathryn Schwartz on May 18, 2014
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The data are drawn from the UK Family Expenditure Survey, which has been collected continuously and consistendy since 1968.2 This gives us a long time-series of data on consumption, a crucial factor in estimating Euler equations and asset pricing models. Changing patterns of direct share ownership over the last twenty years also make the UK an interesting case for analysis. The Conservative government in the early 1980s introduced a number of measures designed to create a ‘share-owning democracy’, including the heavily-advertised flotation of public utilities and tax-breaks for employee share schemes. Largely as a result of these measures, there was a near trebling of the level of share ownership over a very concentrated period, 1985-88. These changes induced a change in the composition of shareholders and may also have changed the nature of the process generating prices and returns. this
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ASSET HOLDING AND CONSUMPTION VOLATILITY: Introduction 2

Posted by Kathryn Schwartz on May 16, 2014
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The time series properties of the consumption growth of a group of individuals classified as shareowners at a single point in time might not be indicative of the properties of the IMRS relevant for past asset prices. This is important in the US, and particularly in the UK, where levels of share ownership and the composition of the group of shareholders have changed dramatically in recent years. this
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ASSET HOLDING AND CONSUMPTION VOLATILITY: Introduction

Posted by Kathryn Schwartz on May 14, 2014
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Asset pricing models based on the Euler equation for consumption have not performed well empirically. One of the reasons put forward has been the lack of variability of the intertemporal marginal rate of substitution of consumption, given plausible parameter values (see, for example, Hansen and Singleton, 1982, or Kotcherlakota, 1996, for a survey).

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CAUSAL EFFECTS IN NON-EXPERIMENTAL STUDIES: Sensitivity to Selection on Observables 2

Posted by Kathryn Schwartz on May 12, 2014
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This paper demonstrates how to estimate the treatment impact in an observational study using propensity score methods.
These methods are assessed using Lalonde’s influential re-creation of a non-experimental setting. Our results show that the estimates of the training effect are close to the benchmark experimental estimate, and are robust to the specification of the comparison group and the functional form used to estimate the propensity score. A researcher using our method would arrive at estimates of the treatment impact ranging from $1,473 to $1,774, very close to the benchmark unbiased estimate from the experiment of $1,794. Click Here
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