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
Test 0.00 0.00 0.00
Weak-ID 23.53 23.42 51.60
Test 16.38 16.38 16.38
R-sq 0.23 0.39 0.30 0.42 0.58 0.60 Note: The number of observation is 82. For the IV estimation, we use SMGAP as the instrument to contorl for the endogeneity related to LEGAP . The top figures are the estimated coefficients, and the bottom figures are heteroskedasticity-robust t-statistics. ***, **, and * respectively indicate the significance level at p<0.01, p<0.05, and p<0.10. Under- ID test: Kleibergen-Paap rk LM statistic at the top, and the corresponding p-value at the bottom (Kleibergen & Paap, 2006). Weak-ID test: Kleibergen-Paap rk Wald F statistic at the top, the Stock-Yogo weak ID test critical value for the Cragg-Donald i.i.d. case for a 10% bias at the bottom (Kleibergen & Paap, 2006; Stock & Yogo, 2005). Eqs. (1-1iv) and (1-2iv) are from Kageyama (2013).
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.
Our empirical approach differs from that of Malvey and Archibald’s and related studies, in that we do not look at when-issued or secondary market prices to assess the “value” of the securities being sold. 3 Indeed, what we are interested is the “inframarginal surplus” of the bidders, which, in the presence of downward sloping demand, will not be apparent from looking at market clearing prices either in the primary or secondary markets. Heterogeneity in valuations that lead to downward sloping demand for these securities may arise from many different sources: buy-and-hold bidders may have idiosyncratic portfolio immunization needs, financial intermediaries may attach different valuations to the Treasuries due to e.g. their use as collateral, primary dealers may value having an inventory of Treasury beyond its resale value because being a primary creates additional value streams (such as complementary services or access to Fed facilities).
III.B. Search Costs/Information Frictions
An additional (but not mutually exclusive from product dif- ferentiation) possible explanation for the observed price disper- sion is the influence of search/information frictions faced by in- vestors. A large theoretical literature shows that costly search can sustain price dispersion in homogeneous product markets (e.g., Burdett and Judd , Carlson and McAfee , and Stahl ). Given the very large number of mutual funds offered, it seems reasonable to presume that investors must make some information-gathering investments before deciding between fund alternatives. The presence of a sizable market to reduce investor search costs supports this notion. Several commercial mutual fund ranking services and information aggregators exist (Morningstar, Lipper, Valueline, Yahoo!Finance, etc.). There is even a commercial Internet site (IndexFunds.com) devoted to providing information about index funds. Many fund companies spend considerable sums on marketing and distribution, also consistent with (although neither necessary nor sufficient for) the presence of limited investor information. Survey evidence also suggests considerable information-gathering. The Investment Company Institute  reports that surveyed investors con- sulted a median of two source types (four for those who had consulted a fund-ranking service) and reviewed a median of four- teen different information items (gross returns, relative perfor- mance, etc.) before their most recent purchase. 14 To the extent
This table reports the coefficients from 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. Distance is average pairwise distance (in 100-mile increments) between all pairs of branches of the failed bank and potential acquirer. Potential acquirer controls (unreported) include Size, Liquidity Ratio, % CRE Loans, % C&I Loans, NPL Ratio, OREO Ratio, Unused Commitment Ratio , and Tier1 Capital Ratio as defined in Table I . Column (1) of Panel A includes failed bank fixed effects and the above potential acquirer controls. The specifications in columns (2) and (3) of Panel A include potential acquirer and potential acquirer-quarter fixed effects, respectively. The introduction of potential acquirer and potential acquirer-quarter fixed effects eliminates observations with invariant dependent variables at the level of the potential acquirer and potential acquirer-quarter, resulting in a reduction in the number of observations from column (1) to columns (2) and (3). Panel B reports results from a fixed effects logit regression using the specification in column (3) of Panel A on coastal/noncoastal areas and on high/low house price growth areas (2001:Q1–2006:Q4). Coastal is an indicator variable taking the value of one if the headquarters of the failed bank is located in a coastal state, where coastal state is defined as any state with a coastline on the Atlantic Ocean, Pacific Ocean, and Great Lakes. High HPI growth is an indicator variable that takes the value of one if the house price index (HPI) growth in the failed bank’s branch service area over the 2001:Q1–2006:Q4 period is greater than the median HPI change for all failed banks. HPI growth is calculated using the all-transactions indexes at the metropolitan statistical area and state nonmetropolitan levels provided by the Federal Housing Finance Agency. We calculate the HPI growth for each failed bank by weighting the HPI growth variable for each bank by the percentage of deposits of the failed bank in each area. Panel C repeats the analysis of column (3) of Panel A after stratifying the sample based on above- and below-median level of CRE, residential, and C&I loans held across the failed banks in the sample. Standard errors are presented in parentheses, and are clustered at the level of the failed bank’s state headquarters. ***, **, and * represent statistical significance at the 1%, 5%, and 10% levels, respectively.
The audit market’s unique combination of features—its role in capital mar- ket transparency, mandated demand, and concentrated supply—means it re- ceives considerable attention from policy makers. We explore the effects of two market scenarios that have been the focus of policy discussions: manda- tory audit firm rotation and further supply concentration due to the exit of a “Big 4” audit firm. To do so, we first estimate publicly traded firms’ demand for auditing services, allowing the services provided by each of the Big 4 to be differentiated products. We then use those estimates to calculate how each scenario would affect client firms’ consumer surplus. We estimate that, for U.S. publicly trade firms, mandatory audit firm rotation would induce con- sumer surplus losses of approximately $2.7 billion if rotation were required after 10 years and $4.7–5.0 billion if after only four years. We find similarly that exit by one of the Big 4 would reduce client firms’ surplus by $1.4–1.8 billion. These estimates reflect only the value of firms’ lost options to hire the exiting audit firm; they do not include likely fee increases resulting from less
“participate,” and make the preference dependent on the number of “participants,” which is the externalities we consider.
To the best of our knowledge, Sasaki and Toda (1996) and Hafalir (2008) are the only papers that investigate a two-sided matching model with externalities. Both papers consider a very general form of externalities. Analyzing such matching models is di¢cult because preference is de…ned over the set of assignments rather than matchings. Hence, regular de…nition of “stability” or “deviation” are not su¢cient to analyze such a model because a deviating pair’s preference also depends on how other agents would react to their deviation, not just their matching. To model how other agents would react to a player’s deviation, both papers use what they call the estimation function approach. Estimation functions specify the expectations on the assignment (i.e., what the matching among all players would be) after each deviation. They prove that a strong requirement on the estimation function is necessary in order to guarantee the existence of stable matching. Based on their estimation function approach while considering a particular form of externalities (the payo¤ depends only on the number of operating …rms in the market), we show the existence and provide characterizations.
• 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