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.
HPGAP are respectively 2 . 97 and - 0 . 07 .
As for LEGAP , we use the difference in life expectancy at birth between women and men. Although this is not a perfect measure to examine the relationship between longevity and happiness because life expectancy 2 The results obtained in the present study are consistent with previous studies, such as Pampel and Zimmer （1989） and Ram （1993） , that employ panel data sets.
deposit-based market concentration. Other failed bank controls include Size, Liquidity Ratio, % CRE Loans, % C&I Loans, NPL Ratio, OREO Ratio, Unused Commitment Ratio, and Tier 1 Capital Ratio . Panel B repeats the analyses of specifications (1) and (2) of Panel A using instrumented values of Tier 1 capital ratio to construct the local capitalization variables. The columns of Panel B present results for different subsamples used in the computation of the instrumental variable (described in the table). Panel C introduces additional controls for the terms of the winning bid. The dependent variable in columns (1) and (2) is Cost, and in columns (3) and (4) is Asset Discount, which is the discount on assets bought by the acquirer minus the premium offered by the acquirer for the deposits of the failed bank (both as a percent of the assets of the failed bank at the time of closure). Bid characteristics include All Bank & All Deposits, which is an indicator variable that takes the value of one if the deal was for all loans and deposits of the failed bank, No Loans & All Deposits, which is an indicator variable that takes the value of one if the deal was for no loans and all deposits of the failed bank, No Loans & Insured Deposits, which is an indicator variable that takes the value of one if the deal was for no loans and only the insured deposits of the failed bank, Loss Share Agreement, which is an indicator variable that takes the value of one if the transaction includes a loss share agreement between the FDIC and the acquirer, and Loss Share % (First Tranche), which is the loss share percentage assumed by the regulator in the first tranche of the loss share agreement. We also include Number of Bids, which captures the number of bids in each P&A transaction. Standard errors are presented in parentheses, and are clustered at the level of the failed bank’s state headquarters. ***, **, and * represent statistical significance at 1%, 5%, and 10% levels, respectively.
market, p j and mc j be the price and (constant) marginal costs for
fund j, and q j be the fund j’s market share given the price and
characteristics of all sector funds. Then the profits of fund j are (8) ⌸ k ⫽ Sq j 共 p, W គ 兲共 p j ⫺ mc j 兲.
dependence of the price elasticity on not just α but also all the other com- ponents of the utility function explains why there are different price elastic- ities for each audit firm. Intuitively, the price elasticity reflects not just how much an auditor’s fee increase would reduce a client firm’s utility if it chose that auditor, but also how likely that client would be to choose that auditor in the absence of that fee increase. For potential clients with preferences that would make them very likely to choose the auditor in the absence of any price increase (having a very strong brand preference for that audit firm, for instance), it is unlikely that the higher fees would change their choice of the auditor. This makes the overall response to a fee increase of such clients—their price elasticity of demand for that auditor—small in magnitude. Similarly, for potential client firms that would be very unlikely to choose the auditor before any price increase (like those with a very weak brand preference for the auditor), higher fees are also unlikely to change their choice, and their elasticity will be small. Thus, the most responsive po- tential clients to a fee increase—those with the highest elasticity of demand for the audit firm—are those with intermediate likelihoods of hiring the au- ditor, as their choice is more likely to be shifted by a fee change. An audit firm’s overall price elasticity across the entire market is the combination of all these price responses across all potential clients. Therefore, even if ev- ery potential client firm’s utility is equally affected by a given fee increase, the wide and varied distribution of probabilities with which various poten- tial clients would choose that auditor implies every auditor faces different price elasticities across individual clients and the market as a whole.
When banks can charge retail fees for cash withdrawal services, they have at least two broad proit motives for adopting ATMs. First, there is the pure stand-alone proit motive associated with the fee revenues from ATM cash withdrawals. Second, there is a strategic motive when the fees come in the form of foreign fees and/or surcharges, i.e., additional fees for consumers using ATMs from banks other than their own. These fees result in partial incompatibility between different ATM networks, providing banks with larger networks a strategic advantage over their rivals, as they can more easily attract new customers, or raise their rivals’ costs. The recent ATM literature has largely focused on these two proit incentives for adopting ATMs, see, e.g., McAndrews (2003) for an overview of the theoretical literature and Hannan et al. (2003), Ishii (2005), Gowrisankaran and Krainer (2007), Hannan and Borzekowski (2007), and Knittel and Stango (2008) for recent empirical contributions.
sector after the collapse of asset prices, as early as 1995, the Ministry of Finance started discussing a Prompt Corrective Action scheme with which the government could order undercapitalized banks to take remedial action. 5 In December 1996, the Ministry of Finance published the basic framework of the Prompt Corrective Action that was set to take effect in April 1998. In preparation, many banks tried to improve their regulatory capital ratio, on which the regulations were based. Because one way to do so was to decrease risky assets such as corporate loans, the government was concerned about creating a credit crunch. Therefore, the government decided to allow some flexibility for banks in the scheme’s implementation. For example, banks were allowed to choose between market and book values for their stocks and real estate holdings so that they did not have to report unrealized losses on securities in their trading account or they could include unrealized capital gains in their real estate assets in their capital. With such changes in place, the government officially introduced the Prompt Corrective Action in April 1998.
al. (2014) also show that optimal bid shading in these auctions also distorts the efficiency of the allocations, and thus a general ranking of expected revenues from discriminatory and uniform price auctions can not be made without knowledge about the specific features of bidder demand.
Given the theoretical vacuum, a variety of empirical approaches have been employed to as- sess the efficacy of Treasury auction mechanisms. The Treasury’s own study of this question, as reported by Malvey and Archibald (1998), was based on experimentation with the uniform price format for 2- and 5-year notes. To assess the revenue properties of the uniform vs. the status-quo discriminatory format, Malvey and Archibald calculated the auction-when-issued rate spread, and did not statistically reject a mean difference across the different auction formats. However, they note that the uniform price auctions “produce a broader distribution of auction awards” across bidders, and especially a lowered concentration of awards to top primary dealers.
Another challenge is an econometric one: the model has multiple equilibria and the parameter cannot be point-identi…ed without imposing some equilibrium selection rules. Instead of imposing equilibrium selection rules, we take the partial-identi…cation approach exploiting the lattice property of the equilibrium. Though the econometrician cannot tell which equilibrium is played in the observed data, the equilibrium characterization provides upper and lower bounds for the equilibrium payo¤s for each …rm. To be more precise, all incumbents have the highest equilibrium payo¤ in incumbent(I)-optimal equilibrium, and the lowest equilibrium payo¤ in potential entrant(E)-optimal equilibrium. All other equilibrium payo¤s are bounded by these two. Hence, the payo¤ corresponding to the observed outcome is bounded above and below by these extremum equilibrium payo¤s, from which we construct moment inequalities for incumbents. Similarly, all potential entrants obtain the highest payo¤ in E-optimal equilibrium and so on. Thus, we can construct moment inequalities using these equilibrium characterizations without the knowledge of the equilibrium selection rule.