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his paper analyses the consumption-investment problem of a loss averse investor equipped with s-shaped utility over consumption relative to a time-varying reference level. Optimal consumption exceeds the reference level in good times and descend to the subsistence level in bad times. Accordingly, the optimal portfolio is dominated by a mean-variance component in good times and rebalanced more aggressively toward stocks in bad times. This consumption-investment strategy contrasts with customary portfolio theory and is consistent with several recent stylized facts about investors' behaviour. I also analyse the joint effect of loss aversion and persistence of the reference level on optimal choices. Finally, the strategy of the loss averse investor outperforms the conventional Merton-style strategies in bad times, but tend to be dominated by the conventional strategies in good times.
This paper addresses whether and to what extent econometric methods used in experimental studies can be adapted and applied to financial data to detect the best-fitting preference model. To address the research question, we implement a frequently used nonlinear probit model in the style of Hey and Orme (1994) and base our analysis on a simulation stud. In detail, we simulate trading sequences for a set of utility models and try to identify the underlying utility model and its parameterization used to generate these sequences by maximum likelihood. We find that for a very broad classification of utility models, this method provides acceptable outcomes. Yet, a closer look at the preference parameters reveals several caveats that come along with typical issues attached to financial data, and that some of these issues seems to drive our results. In particular, deviations are attributable to effects stemming from multicollinearity and coherent under-identification problems, where some of these detrimental effects can be captured up to a certain degree by adjusting the error term specification. Furthermore, additional uncertainty stemming from changing market parameter estimates affects the precision of our estimates for risk preferences and cannot be simply remedied by using a higher standard deviation of the error term or a different assumption regarding its stochastic process. Particularly, if the variance of the error term becomes large, we detect a tendency to identify SPT as utility model providing the best fit to simulated trading sequences. We also find that a frequent issue, namely serial correlation of the residuals, does not seem to be significant. However, we detected a tendency to prefer nesting models over nested utility models, which is particularly prevalent if RDU and EXPO utility models are estimated along with EUT and CRRA utility models.
We designed and fielded an experimental module in the 2014 HRS which seeks to measure older persons’ willingness to voluntarily defer claiming of Social Security benefits. In addition we evaluate the stated willingness of older individuals to work longer, depending on the Social Security incentives offered to delay claiming their benefits. Our project extends previous work by analyzing the results from our HRS module and comparing findings from other data sources, which included very much smaller samples of older persons. We show that half of the respondents would delay claiming if no work requirement were in place under the status quo, and only slightly fewer, 46 percent, with a work requirement. We also asked respondents how large a lump sum they would need with or without a work requirement. In the former case, the average amount needed to induce delayed claiming was about $60,400, while when part-time work was required, the average was $66,700. This implies a low utility value of leisure foregone of only $6,300, or about 10 percent of older households’ income.
The global financial crisis and the ensuing criticism of macroeconomics have inspired researchers to explore new modeling approaches. There are many new models that deliver improved estimates of the transmission of macroeconomic policies and aim to better integrate the financial sector in business cycle analysis. Policy making institutions need to compare available models of policy transmission and evaluate the impact and interaction of policy instruments in order to design effective policy strategies. This paper reviews the literature on model comparison and presents a new approach for comparative analysis. Its computational implementation enables individual researchers to conduct systematic model comparisons and policy evaluations easily and at low cost. This approach also contributes to improving reproducibility of computational research in macroeconomic modeling. Several applications serve to illustrate the usefulness of model comparison and the new tools in the area of monetary and fiscal policy. They include an analysis of the impact of parameter shifts on the effects of fiscal policy, a comparison of monetary policy transmission across model generations and a cross-country comparison of the impact of changes in central bank rates in the United States and the euro area. Furthermore, the paper includes a large-scale comparison of the dynamics and policy implications of different macro-financial models. The models considered account for financial accelerator effects in investment financing, credit and house price booms and a role for bank capital. A final exercise illustrates how these models can be used to assess the benefits of leaning against credit growth in monetary policy.
This paper studies the role of the Community Reinvestment Act (CRA) in the recent US housing boom-bust cycle. Using a difference-in-differences matching estimation, I find that the enhancement of CRA enforcement in 1998 caused a 7.7 percentage points increase in annual growth rate of mortgage lending by CRA-regulated banks to CRA-eligible census tracts relative to a group of similar-income CRA-ineligible census tracts within the same state. Financial institutions which are not subject to the CRA, however, do not show any change in their mortgage supply between these two types of census tracts after 1998. I take advantage of this exogenous shift in mortgage supply within an instrumental variable framework to identify the causal effect of mortgage supply on housing prices. I find that every 1 percentage point higher annual growth rate of mortgage supply leads to 0.3 percentage points higher annual growth rate of housing prices. Reduced form regressions show that CRA-eligible neighborhoods experienced higher house price growth during the boom and sharper decline during the bust period. I use placebo tests to confirm that this effect is in fact channeled through the shift in mortgage supply by CRA-regulated banks and not by unobserved demand factors. Furthermore, my results indicate that CRA-induced mortgages went to borrowers with lower FICO scores, carried higher interest rates, and encountered more frequent delinquencies.
The eurozone remains in a deep, largely macro-economic crisis. A robust global economy and falling oil prices have supported Europe’s economy for some time, but by now it is clear that the eurozone will only be able to pull itself out of this crisis by means of more decisive action. One response, the recent easing of monetary policy by the European Central Bank (ECB), has, for the most part, been sharply and one-sidedly criticised in Germany. Monetary policy inaction seems to be the preferred option of many in Germany.
The authors discuss the following question: What would happen if the ECB failed to respond to the excessively low inflation and the weak economy? And what economic policy would be suitable under the current circumstances, if not monetary policy?
We study whether the presence of low-latency traders (including high-frequency traders (HFTs)) in the pre-opening period contributes to market quality, defined by price discovery and liquidity provision, in the opening auction. We use a unique dataset from the Tokyo Stock Exchange (TSE) based on server-IDs and find that HFTs dynamically alter their presence in different stocks and on different days. In spite of the lack of immediate execution, about one quarter of HFTs participate in the pre-opening period, and contribute significantly to market quality in the pre-opening period, the opening auction that ensues and the continuous trading period. Their contribution is largely different from that of the other HFTs during the continuous period.
Non-bank (-balance sheet) based financial intermediation has become considerably more important over the last couple of decades. For the U.S., this trend has been discussed ever since the mid-1990s. As a consequence, traditional monetary transmission mechanisms, mainly operating through bank balance sheets, have apparently become less relevant. This in particular applies to the bank lending channel. Concurrently, recent theoretical and empirical work uncovered a "risk-taking channel" of monetary policy. This mechanism is not confined to traditional banks but has been found to operate also across the spectrum of financial intermediaries and intermediation devices, including securitization and collateralized lending/borrowing. In addition, recent empirical evidence suggests that the increasing importance of shadow-banking activities might have given rise to a so-called "waterbed effect". This is a mediating mechanisms, dampening or counteracting typically to be expected reactions to monetary policy impulses. Employing flow-of-funds data, we can document also for the Euro Area that a trend towards non-bank (not necessarily more 'market'-based) intermediation has occurred. This is, however, a fairly recent development, substantially weaker than in the U.S. Nonetheless, analyzing the response of Euro Area bank and nonbank financial intermediaries to monetary policy impulses, we find some notable behavioral differences between mainly deposit-funded and more 'market'-based financial intermediaries. We also detect, inter alia, the existence of a (still) fairly weak, but potentially policyrelevant, "waterbed" effect.
Households buy life insurance as part of their liquidity management. The option to surrender such a policy can serve as a buffer when a household faces a liquidity need. In this study, we investigate empirically which individual and household specific sociodemographic factors influence the surrender behavior of life insurance policyholders. Based on the Socio-Economic Panel (SOEP), an ongoing wide-ranging representative longitudinal study of around 11,000 private households in Germany, we construct a proxy to identify life insurance surrender in the data. We use this proxy to conduct fixed effect regressions and support the results with survival analyses. We find that life events that possibly impose a liquidity shock to the household, such as birth of a child and divorce increase the likelihood to surrender an existing life insurance policy for an average household in the panel. The acquisition of a dwelling and unemployment are further aspects that can foster life insurance surrender. Our results are robust with respect to different models and hold conditioning on region specific trends; they vary however for different age groups. Our analyses contribute to the existing literature supporting the emergency fund hypothesis. The findings obtained in this study can help life insurers and regulators to detect and understand industry specific challenges of the demographic change.
We introduce long-run investment productivity risk in a two-sector production economy to explain the joint behavior of macroeconomic quantities and asset prices. Long-run productivity risk in both sectors, for which we provide economic and empirical justification, acts as a substitute for shocks to the marginal efficiency of investments in explaining the equity premium and the stock return volatility differential between the consumption and the investment sector. Moreover, adding moderate wage rigidities allows the model to reproduce the empirically observed positive co-movement between consumption and investment growth.