内生変数 ( モデル内で決まる変数 ) ： Y : GDP 、 R: 利子率。小文字の変数は外生変数 ( モデル外で数値が与えられる変数 )
IS ： C : 消費、 I : 投資、 G : 政府支出、 T : 税金、 N X : 純輸出、 EX : 輸出、 IM : 輸入、
a : 基礎消費、 b : 限界消費性向、 m : 限界輸入性向、 i : 基礎投資、 d : 正の定数、 g : 基礎輸出、 n : 正の定数 LM ： M s
This has two implications. First, parents use the same income-dependent relative preferences to measure their children’s well-being. Second, since parents obtain their own utility from consumption in adulthood, they care about their children’s consumption in their adulthood. To capture this latter aspect, I assume that parents are concerned with children’s growth that signals the children’s consumption in adulthood and measure children’s growth with educational output.
This is rooted in the findings in Kageyama
（2012） , which empirically showed that the relationships between LEGAP and these happiness indicators are bidirectional. In one direction, LEGAP negatively affects both HPN and HPGAP . An increase in LEGAP raises women ’ s widowhood ratio, and, since widows are, on average, less happy, it lowers women ’ s average happiness, HPN, and HPGAP . We call this effect the “ marital-status composition effect ” as the marital-status composition plays a central role.
This paper models the strategic behavior of auction participants, and offers model-based quan- titative benchmarks for assessing the competitiveness and cost-effectiveness of this important mar- ketplace. Our model builds on the seminal “share auction” model of Wilson (1979) in which bidders are allowed to submit demand schedules as their bids. This model captures the strategic complexity of the Treasury’s uniform price auction mechanism very well, and it is in many ways related to classic models of imperfect competition such as Cournot. In particular, consider a setting (depicted in Figure 1) where an oligopsonistic bidder with downward sloping demand for the security knows the residual supply function that she is facing, and is allowed to submit a single price-quantity point as her bid. Following basic monopsony theory, this bidder will not select the competitive outcome (P comp , Q comp ), which is the intersection of her demand curve and the residual supply
and significant. This result suggests that banks’ BCR matters in firms’ investment decisions when firms are productive and thus have higher demand for investment. Using the estimated model, we conduct counterfactual experiments to quantify the effect of capital injections that took place in March 1998 and 1999 in Japan. The counterfactual experiments suggest that the capital injections had a negligible impact on the average investment rate, although there is a reallocation effect, with investment shifted from low- to high-productivity firms. The paper most closely related to ours is that of GS, who also examine the effects of bank recapitalization policies on the supply of credit and client firm performance, including firm investment, using matched firm–bank data from the Japanese banking crisis. The authors find that the size of the capital injection is important for its success: If capital injections are large enough so that recapitalized banks achieve capital requirements, such banks increase the supply of credit and firms that borrow from the recapitalized banks increase their investment. This paper’s contribution beyond that of GS is as follows. First, we examine whether firms’ loan and investment responses to their banks’ recapitalization depend on their TFP. This question naturally arises because, theoretically, the higher firm productivity, the larger firm investment and the demand for external finance tend to be. Therefore, bank lending attitude, which likely depends on BCR under the banking regulation, may be more important for high-productivity firms. The finding that high-productivity firms increase their investments more than low-productivity firms in response to their associated banks’ recapitalization would suggest that the resource is allocated toward more productive firms as a result of capital injection. 3 Second, we use the BCR as the main variable to
• We have assumed that there is only one hedge fund style. What might change if we consider multiple hedge fund styles in the model industry? If the manager’s talent also involves an aptitude for one style over another, then this would be equivalent to having several styles calibrated independently. Since the policy results hinge on broad features of the model and the data, the outcomes of policy experiments are unlikely to change much. The only difference is that some styles tend to rely more heavily on leverage than others, so those are more likely to be hurt by leverage limits. In the working version of the paper, we show that most styles have reported leverage around 1. Out of the fourteen styles considered, four report leverage of around 2 (Convertible Arbitrage, Fixed Income, Equity Market Neutral and Relative Value), and three styles report leverage higher than 2 (Fixed income arbitrage, CTAs and CPOs). Table 8 shows the impact of a leverage cap of 1 on the industry
Financial Health of Local Banks and Failed Bank Acquisition Likelihood
This table reports results of a fixed effects logit regression. The dependent variable Pr(acquisition) takes the value of one if potential acquirer j acquires failed bank i and zero otherwise. Tier 1 Capital Ratio (potential acquirer) is the Tier 1 capital ratio of the potential acquirer. Leverage Ratio (potential acquirer) is the common leverage ratio of the potential acquirer (the ratio of Tier 1 (core) capital and (adjusted) total assets). Distance is the average pairwise distance (in 100-mile increments) between all pairs of branches of the failed bank and potential acquirer. Distance (% CRE Loans) is the absolute difference between the failed bank’s and the potential acquirer’s percentage of total loans held in CRE loans. HHI is the average increase in local deposit market concentration that would result from potential acquirer j acquiring the branch network of failed bank i. HHI ranges from 0 to 1,000, where 0 indicates a merger that does not increase local market concentration and 1,000 indicates a merger that transforms a perfectly competitive local market into a local monopoly. P50 Tier 1 Capital Ratio of Local Potential Acquirers is the median Tier 1 capital ratio of the failed bank’s local potential acquirers. Local potential acquirers are potential acquirers whose branch network overlaps in at least one zip code with the branch network of the failed bank. % Well-Capitalized Local Potential Acquirers is the percentage of local potential acquirers whose Tier 1 capital ratio is above the median Tier 1 capital ratio across local potential acquirers. P50 Tier 1 Capital Ratio Close CRE Potential Acquirers is the median Tier 1 capital ratio in the group of close CRE potential acquirers. Close CRE potential acquirers are potential acquirers within the first quartile of loan portfolio closeness according to the CRE distance metric. % Well-Capitalized Close CRE Potential
in X j . There are dummies indicating whether a fund charges a
load, and if it is a rear or deferred load. Loads are a pricing element (which we have already amortized into the price mea- sure), but they also indicate funds sold with bundled broker services that investors may value. Rear or deferred loads indicate the presence of formal switching costs to removing assets from the fund. We also include a dummy if the fund is an exchange- traded fund (i.e., SPDRs or Barclay’s iShares) to control for the special liquidity and intraday pricing features of ETFs. We mea- sure the number of additional share classes attached to the fund’s portfolio; for a single-share-class fund this value is zero. The number of other funds managed by the same management com- pany is included to capture any value from being associated with a large fund family. Fund age is in the regressions as well. (Here, both the number of family funds and age enter in logs to parsimoniously embody diminishing marginal effects. Recall that we instrument for age because of its possible correlation with unobservable quality.) We add the current fund manag- er’s tenure, measured in years, as a covariate. And while all of the funds in our sample seek to match the return profile of the S&P 500 index, they do exhibit some small differences in their financial characteristics. These can result from skilled trading activities by a fund’s management despite having a severely constrained portfolio. We thus include measures of tax expo- sure (the taxable distributions yield rate), the yearly average of the ratio of monthly fund returns to those of the S&P 500 index, and the standard deviation of monthly returns. To the extent that fund buyers prefer any persistent positive varia- tions in financial performance, these controls should capture much of this effect. 32