Finance as a barrier to entry: U.S. bank deregulation and volatility

Transcription

1 Finance as a barrier to entry: U.S. bank deregulation and volatility Viktors Stebunovs Boston College November 10, 2006 Abstract Banks are the largest suppliers of debt capital to small firms, which produce half of U.S. output. In the data, lower bank concentration and branching deregulation are associated with more firms in operation and smaller average firm size. The period of drastic bank deregulation, which started in 1977, coincides with a decline in firm level and aggregate volatility. I examine whether deregulation can account for this volatility decline by reducing bank local monopoly power. In my dynamic, stochastic, general equilibrium model bank market power determines firm concentration. The model predicts an increase in the number of firms and a decrease in firm size after deregulation. Over the business cycle, weaker banking competition implies more vigorous firm entry, more countercyclical firm markups, and stronger substitution effects in labor supply decision. As a consequence, firm entry and output, labor supply, consumption, investment, and aggregate output are all less volatile after deregulation. I thank my advisors, Fabio Ghironi, Peter Ireland, and Matteo Iacoviello for advice and support; Ingela Alger, Fabio Schiantarelli, Susanto Basu, Andrea Raffo, Jonathan Willis, Jordan Rappaport, Giovanni Lombardo, John Leahy, Stephanie Schmitt-Grohe, and Phillip Strahan for helpful conversations. I also thank participants in the thesis and R@BC workshops at Boston College, and in seminars at the Monetary Policy Strategy division at the ECB and at the Economic Research department at the Federal Reserve Bank of Kansas City. I gladly acknowledge the hospitality of Economic Research department at the FRB of Kansas City (Summer 2006) and the the Monetary Policy Strategy division at the ECB (Summer 2005). Department of Economics, Boston College, 140 Commonwealth Avenue, Chestnut Hill, MA 02467, address: stebunov@bc.edu, theurl:<www2.bc.edu/~stebunov> 1

2 1 Introduction Small firms, that produce half of U.S. economy s output, tend to depend on local external sources of finance. 1 Commercial banks are the largest suppliers of debt capital to these firms. 2 The empirical evidence shows that in U.S. local markets with concentrated banking, potential entrants face greater difficulty gaining access to credit than in markets where banking is more competitive. For example, Cetorelli and Strahan (2006) find that lower local bank concentration and looser restrictions on geographical expansion are associated with more firms in operation and smaller average firm size. 3 Hence,theexerciseof monopoly power by banks has the potential to influence a large fraction of U.S. GDP through bank-firm interactions. In turn, I focus on the bank market power as a determinant of firm concentration and its implications for business cycle dynamics in general equilibrium framework. U.S. banking system was once extremely fragmented. Every state in the country barred banks from other states, so instead of one national banking system there were 50 small banking systems, one per state. Most states also prohibited branching into other cities within the state, so there were countless small banking systems, one per city (Morgan et al, 2004). A period of dramatic state-level deregulation started in The deregulation of restrictions on banks ability to expand across local markets was completed with the passage of the Riegle - Neal Interstate Banking and Branching Efficiency Act in Since then it becomes increasingly less plausible to view banking markets as local, both because of the deregulation and the onset of new lending technologies that allow long distance lending (Cetorelli and Strahan, 2006). The deregulation of restrictions on bank expansion, both within and across states, has been shown to limit bank market power. Jayarante and Strahan (1998) and Dick (2006) find that loan prices and bank spreads declined after deregulation. Black and Strahan (2002) find that the rate of new incorporations increased following deregulation of branching restrictions, and that deregulation reduced the negative effect of concentration on new incorporations. They also find the formation of new incorporations increased as 1 The research on bank market power suggests that the relevant geographical market for banking services, especially for small firms or potential entrepreneurs, is local. See, for example, Berger et al (1999). 2 Based on the Survey of Small Business Finances, Berger and Udell (1998) show that commercial banks provide on average over 18% of total equity plus debt and other financial intermediaries provide additional 6%. There are considerable differences across firms though. For example, commercial banks alone provide over 30% of total equity plus debt for 3-4 year old firms. Turning to particular kinds of credit, commercial banks supply more than 80% of lending in the credit line market and more than 50% in other markets, such as commercial mortgages and vehicle, equipment, and other loans (U.S. Small Business Administration). 3 They find no effect of changes in banking competition, however, on the largest firms, which is reasonable given that these firms have access to nationwide securities markets. The non-financial sector is represented by a panel data set from the County Business Patterns of manufacturing establishments in operation across U.S. states between 1977 and

3 the share of small banks decreased, suggesting that diversification benefits of size outweighed the possible comparative advantage small banks might have had in forging lending relationships. Correa (2006) finds that the interstate bank integration decreased financing constraints, with small firms benefiting the most. 4 In what follows I concentrate on privately held firms, that tend to depend on local external sources of finance. 5 The number of privately held firms increased by over 34% between 1980 and 2000 (Davis et al, 2006). Their share of employment in total employment increased by nearly 3 percentage points to 74%. The average firm size, measured by average firm employment scaled by GDP, declined by about 36%. 6 Contrary to the earlier studies, that focused solely on publicly traded firms, recent research finds that U.S. firms became significantly more stable in the past 25 years. 7 Davis et al (2006) find opposing trends in the volatility of publicly traded and privately held firms. Their results show that while the rise in volatility among publicly traded firmsissignificant, it is not large enough to offset the decline in volatility among privately held firms, which is of the magnitude of either 18% or 50% depending on the measure used. 8 An important factor in the decline in volatility is the slow down in the pace of business entry and exit by more than 40%. The decline in firm level volatility coincides with the great moderation in aggregate volatility, see Table 6 in Appendix. The decline in volatility of GDP can be traced to a number of causes, including the decrease in volatility of personal consumption expenditures and non-residential fixed investment. The decline in volatility of total private hours and in net firm entry is also remarkable. 9 Precisely how financial deregulation affects volatility, that is, by what channel, is far from obvious. In this paper I investigate just one possible channel linking the reduction in bank monopoly power to economic fluctuations. I examine whether Cetorelli and Strahan (2006) finding can be explained in general equilibrium framework, whether financial deregulation can account for the decline in firm level and aggregate volatility by reducing bank local monopoly power This paper uses data on publicly-traded firms in the U.S. though. 5 Irealizethattherearefewlargeprivatelyheldfirms in U.S. economy, for example family-controlled S.C. Johnson Co., that compete on national rather than local market and have access to national securities market. Nevertheless, small firms with fewer than 500 employees represent 99.7% all employer firms, employ half of all private sector employees, pay more than 45% of total U.S. private payroll, have generated 60 to 80% of net new jobs annually over the last decade, and produce more than 50% of non-farm private GDP (U.S. Small Business Administration). 6 The average firm size, measured by average firm employment, increased from 14.6 to 17.7 employees (Davis et al, 2006). The average firm size scaled by U.S. population declined by 2.7%. 7 Comin and Mulani (2003) or Comin and Philippon (2005) report the rise in publicly traded firm volatility. 8 The first measure includes short lived firms, the second measure includes firms with the lifespan of 10 years or more. 9 Net firm entry is defined as the difference of new business incorporations and business failures. See Table 7 in Appendix for details. 10 Philippon (2003) stresses the role of competition in goods market behind the increase in volatility for publicly traded firms. In his model, an unexplained change in competition pressure leads to a higher frequency of price adjustments and hence higher sales volatility. In turn, more frequent price adjustments dampen the economy response to aggregate demand 3

4 I develop a flexible-price, dynamic, stochastic general equilibrium (DSGE) model of the macroeconomy with a monopolistic banking sector. The model is based on the framework of Ghironi and Melitz (2005) and Bilbiie et al (2006), where monopolistic firm entry is subject to sunk cost and time-to-build lag. The number of firms is an endogenous state variable, consistent with the notion that the number of producing firms is fixed in the short run. 11 In the model investment is accounted for by the creation of new firms. The model incorporates the premise, proposed by Cestone and White (2003), that entry deterrence takes place through financial rather than product markets. In the model banks with market power erect a financial barrier to firm entry to protect the profitability of their existing borrowers. The bank concentration is exogenous to the business cycle. 12 The model predicts that bank deregulation generates an increase in the long run number of firms, a decrease in firm size, an increase of the investment share in the economy, an increase in labor supply, and a decrease in firm and bank markups. The model generates procyclical firm entry and countercyclical firm and bank markups. 13 Over the business cycle, driven by a favorable aggregate productivity shock, bank monopoly power implies more vigorous firm entry, more countercyclical firm markups, and stronger substitution effects (and weaker income effects) in labor supply decision. 14 As a consequence, firm entry and output, labor supply, consumption, investment, and aggregate output are less volatile after deregulation. I do not attempt to replicate exactly the levels of second moments, just the changes in second moments. The channel identified in the context of the tractable DSGE model appears to be sufficiently powerful to merit serious empirical investigation in future research. I emphasize that I do not discount the role of other explanations of the volatility decline observed in the data, such as the run of good luck in stochastic shocks (Stock and Watson, 2002). There might be alternative structural explanations of the decline in firm and aggregate volatility as well. For example, an alternative channel might work through the interplay of a collateral requirement for firm start-up loans and labor supply. 15 Financial deregulation might lead to a decline in labor supply volatility by lowering the collateral requirement, and hence lead to a decline in firm level and aggregate volatility. shocks. Having the business cycle driven by demand shocks is crucial in his setup, as nominal rigidities tend to dampen supplies shocks. 11 This is in contrast to other recent contributions, such as Comin and Gertler (2006) and Jaimovich (2006), whose entry mechanisms allow instantaneous variation in the number of producing firms. 12 As shown in Stebunovs (2007), there is some indication that the bank market structure became endogenous to the business cycle. In the late 1970s bank branch movement turned from acyclical to countercyclical. 13 In the data firm entry is procyclical, see Chatterjee and Cooper (1993) or Devereux et al (1996), and bank loan markups are countercyclical, see Dueker and Thornton (1997). 14 Domowitz et. al. (1988) document more countercyclical markups in concentrated industries. 15 This channel is similar to the one studied by Campbell and Hercowitz (2006) in the case of household borrowing. 4

5 The remainder of the paper is organized as follows. Section 2 presents the benchmark model. Section 3 discusses some key properties of the model and solves for its steady state. Section 4 shows dynamic properties of the model for transmission of an aggregate productivity shock by computing impulse responses and second moments. Section 5 discusses the extended model, computes impulse responses and changes in second moments, and suggests the complementary collateral channel. Section 6 concludes. A section in Appendix gives more details on the effects of branching deregulation, including the effects on loan prices, deposit rates, and bank spreads. 2 Benchmark model There are three classes of agents in the economy: households, banks, and firms. There are several exogenously given locations with a number of banks and a continuum of firms at each of them. 16 Each location bears some similarity to Salop (1979) circle commonly used in the banking literature. Figure 1 illustrates the representative location setup. i th bank ω th firm local goods market Figure 1: Representative location with H =4banks and a local goods market. Each firm is monopolistic, produces one consumption variety, competes in a local market, has no collateral to pledge except a stream of future profits, and its entry is subject to a sunk entry cost. The model reflects the notion that small firms tend to patronize a local bank. 17 Unspecified financial frictions 16 In the model the boundaries of product markets and lending markets coincide. However, in reality some larger firms may span multiple banking markets. In such cases, a bank could still have an impact on entry within its area of influence. 17 This assumption rules out bundling the entry loan amount over several banks, and thus precludes risk sharing among 5

6 force a prospective entrant to borrow the amount necessary to cover the sunk entry cost from a nearby bank rather than to raise funds directly in an equity market. I assume that sufficiently high switching cost inhibit prospective entrants from borrowing from a distant bank at the same location. 18 Before deregulation borrowing at a different location is prohibited altogether. Firm entry reduces the stream of future profits of both incumbents and entrants and thus the amount pledgeable for entry loan repayments. Each bank, being a local monopolist, is able to extract all the profits from a prospective entrant, holds a portfolio of firms and decides on the number of loans to be issued (that is, on the number of entrants). 19 Each bank trades the increase in revenue from expanding its firm portfolio (portfolio expansion effect) against the decrease in revenue from all firms in its portfolio due to stronger firm competition (profit destruction effect). The profit destructioneffect gives rise to credit rationing on the extensive margin as not all of the prospective entrants will be funded. Thus, there is an intrinsic inefficiency built into the model due to the presence of monopolistic banks. 20 Each bank supplies real one-period deposits to households in a perfectly competitive national market. The bank then uses the deposits to fund firm entry. Thus, the cost that each bank faces is the deposit interest rate. Since the completion of financial deregulation in 1994, it becomes increasingly less plausible to view banking markets as local. Banks ability to expand across local markets and new technologies, that allow banks to lend to distant borrowers, limited incumbent banks local monopoly power. 21 Consequently, I model bank deregulation as lifting the restriction on borrowing from a bank at a different location. The number of banks in the economy might stay the same or decrease. However, the number of banks represented locally increases. In what follows, for expositional simplicity, I present the economy with one location only. 22 banks. The bundling might function similarly to loan syndication that became widespread in the early 1990s. 18 Modelling switching costs explicitly is not necessary. I assume that firms borrow only once to cover the entry cost. Banks are symmetric, price entry loans the same way, there is no room for arbitrage and hence entry loan refinancing is not possible. 19 Banks compete in the number of entrants in Cournot fashion as in the static partial equilibrium model of Gonzalez- Maestre and Granero (2003). 20 If one interprets the number of firms as the number of production lines in the economy, then a bank might be thought as of a multi-production line company that produces a set of goods that compete within this set and also with goods produced by other multi-production line companies. Then each multi-production line company internalizes only its own product cannibalization. 21 Black and Strahan (2002) argue that after deregulation, the effects of concentration ought to have been mitigated by the threat of entry. That is, banking concentration no longer signals market power when barriers to entry from regulations have been eliminated. And, in fact, they find that the effect of concentration on the rate of creation of new incorporations does fall significantly with deregulation. 22 I conjecture that the predictions will remain the same in the multi-location model. 6

7 2.1 Households The economy is populated by a unit mass of atomistic households. All contracts and prices are written in nominal terms, prices are flexible, and money is just a unit of account for contracts. Each household supplies l units of labor inelastically and maximize expected intertemporal utility from consuming the basket C, X E t s=t β s t Cs 1 γ 1 γ where β (0, 1) is the discount factor and γ > 0 is the inverse of the intertemporal elasticity of substitution, subject to a budget constraint. Households enjoy variety. continuum of goods Ω, Households consume the basket of goods at time t, C t,defined over a µz C t = ω Ω θ c t (ω) θ 1 θ 1 θ dω, where θ > 1 is the symmetric elasticity of substitution across goods. At any given time t, only a subset of goods Ω t Ω is available. Let p t (ω) denote the nominal price of a good ω Ω t. The consumption based price index is then given by and the household s demand for each variety ω is µz 1 P t = p t (ω) 1 θ 1 θ dω, (1) ω Ω t µ θ pt (ω) c t (ω) = C t =(ρ t (ω)) θ C t, (2) P t where ρ t (ω) =p t (ω)/p t is the relative price of variety ω. Households hold two types of assets: shares in a mutual fund of H banks, s t, and one-period deposits, B t. The mutual fund pays a total profit in each period (in units of currency) equal to the total profit of all banks, P t Pi H π t(i), whereπ t (i) denotes the profit ofbanki. During period t, the representative household buys s t+1 shares in the mutual fund of H banks. The date t price in units of currency of a claim to the future profit stream of the mutual fund of H banks is equal to the nominal price of claims to future bank profits, P t Pi H v t(i), wherev t (i) is the price of claims to future profits of bank i. Hence, 7

8 the period budget constraint in units of consumption is: X X B t + s t v t (i)+c t =(1+r t 1 )B t 1 + s t 1 (π t (i)+v t (i)) + w t l, (3) i H i H where r t 1 is the consumption based interest rate on deposits between t 1 and t (known with certainty as of t 1), and w t is the real wage. The Euler equations for deposits and share holdings are, respectively: " µct+1 # γ 1=β(1 + r t )E t, C t and " µct+1 γ v t = βe t (π t+1 + v t+1)#, (4) C t where v t = P i H v t(i) and π t+1 = P i H π t+1(i). Forward iteration of the Euler equation for shares holdings gives the value of the mutual fund, v t, in terms of a stream of bank profits, π t. 2.2 Firms There is a mass of monopolistic firms, N t,ineachperiodt; N t is the mass of the set Ω t Ω. Eachfirm produces one different variety, ω Ω, with a linear production function, y t (ω) =Z t l t (ω) where Z t is exogenous aggregate productivity, and l t (ω) is labor demand. The unit cost of production (marginal cost), in units of the consumption good is w t /Z t. Exogenous aggregate productivity follows an autoregressive process of order one, AR(1), with the persistence parameter ϕ Z. Each firm ω faces demand given by equation (2) and sets its price in a flexible fashion as a constant markup over marginal cost. In units of consumption, firm ω s price is ρ t (ω) = θ w t = µ F w t. (5) θ 1 Z t Z t where ρ t (ω) is the relative firm ω price, and µ F = θ/ (θ 1) is the firm markup over the marginal cost. 8

9 The period profit in units of consumption is given by d t (ω) = 1 θ ρ t(ω) 1 θ C t. Firm prices, quantities, and profits follow from the post entry firm s problem after imposing symmetry. There are no idiosyncratic shocks, all firms face the same marginal cost and the same demand. Hence, equilibrium prices and quantities are identical across firms: p t (ω) =p t, ρ t (ω) =ρ t,l t (ω) =l t,d t (ω) =d t. The firm price under symmetry is such that: 23 ρ t = N t 1 θ 1. An increase in the number of firms implies necessarily that the relative price of each good increases. When there are more firms, households derive more welfare from spending a given nominal amount, ceteris paribus, the price index decreases, and the relative price of each good must rise. A potential entrant faces a sunk entry cost and has to borrow from a bank to cover this cost. An entrant can pledge up to d t in entry loan repayments post entry in each period t, d t = 1 θ ρ t 1 θ C t = 1 θ C t N t. (6) Since the bank has all the bargaining power, it sets the periodic entry loan repayment at d t to extract all the profit, and the entrant accepts that. 24 Entrants are sufficiently small and take the aggregate consumption, C t, as given. Hence, the expression (6) yields an inverse relationship between the mass of incumbent firms in the economy, N t, and the loan repayment, d t. The resulting firms willingness to pay for entry depends on the mass of firms. 23 This equation follows from the price index under symmetry, see the equation (1). 24 The modelling strategy precludes interpreting the financial contract as debt, as the entry loan repayments are not firm state dependent. Although the assumption that banks have bargaining power and are able to extract all the profit maybe unrealistic, it simplifies the model solution substantially. It is not necessary to keep track of outstanding loan amounts for each firm generation, and firms of different vintages can be treated equally. This modelling strategy also allows the model to reproduce the apparent absence of pure profits in U.S. industries despite the presence of market power (even in the short run). 9

10 2.3 Banks The fixed number of banks, H, competes in Cournot fashion in each period t. 25 Each bank i acts on the expectation that its own decision will not affect decisions of its rivals. The bank i decides simultaneously with other banks on the number of entrants to be funded, k t (i), taking into account: (1) limited liability periodic repayments of the entry loan are at most equal to firm profits; (2) goods market clearing all firms compete in the local market, where firm prices, quantities, and profits are determined; and (3) post entry firm profit maximization each firm sets an optimal price for its variety. In every period t, thereisamassoffirms, K t (i), in each bank i s portfolio, a mass N t of firms in the economy, and an unbounded number of prospective entrants around each bank i. Each bank i takes the aggregate variables, C t, w t,andr t, as given. The bank correctly anticipates expected future firm profit, d s, in every period s t +1, and takes into account the exogenous probability δ of the firm exit inducing shock. Entrants at time t only start producing at time t +1, which introduces a one period time-to-build lag in the model. The exogenous exit shock occurs at the end of each period. Therefore, a proportion δ of period t entrants will never produce and will exit within the period. 26 The assumed timing of entry and production implies that the number of producing firms in period t, N t, is an endogenous state variable that behaves like physical capital in standard real business cycle (RBC) models. The household s Euler equation for shares, equation (4), implies the objective function for each bank i: max E t {K s+1 (i),k s (i)} s=t X s=t µ γ β s t Cs π s (i). C t Bank i s profit, π t (i), isgivenby π t (i) =K t (i)d t + B S t (i) w t Z t k t (i) (1 + r t 1 ) B S t 1(i), (7) where d t K t (i) isthereturnfrombanki s portfolio of K t (i) incumbent firms, B S t (i) is the amount of household deposits in period t into bank s i, wt Z t k t (i) istheamountlenttok(i) entrants, and (1 + r t 1 ) Bt 1(i) S is the principal and interest on the period s deposits. Equation (6) gives the periodic entry loan repayment, d t. Each bank i accrues portfolio returns after firm entry has been funded and then rebates its 25 As will become clear later, this is not exactly the Cournot model as not only the value of entrants, but also the value of incumbents depends on the number of entrants. 26 In the data business failures are countercyclical (Cooper and Chatterjee, 1993, and Devereux et al, 1996). Although, an endogenous exit rate would help explain the slow down in firm turnover reported by Davis et al (2006), introducing it would complicate the model considerably, see Stebunovs (2007). 10

11 profits to the mutual fund owned by households in each period t. Thus,bank i s balance sheet constraint is: B S t (i) = w t Z t k t (i). I assume that the sunk entry cost per entrant in units of effective labor is one, and hence the sunk entry cost in units of consumption is w t /Z t, which varies with the business cycle. The law of motion of the firm portfolio of bank i is: K t (i) =(1 δ)(k t 1 (i)+k t (i)), (8) Aggregation across banks gives the overall mass of incumbent firms in the economy in a period t, N t = P i H K t(i), the overall mass of entrants n t = P i H k t(i), and the law of motion of the overall mass of firms in the economy, N t =(1 δ)(n t 1 + n t 1 ). (9) First order condition with respect to K t+1 (i) gives the Euler equation for firm value to bank i, q t (i), and involves a term capturing the internalization of the profit destruction externality (PDE): 27 q t (i) =βe t µ Ct+1 C t γ d t+1 + K t+1 (i) d t+1 N t+1 +(1 δ)q t+1 (i) N t+1 K t+1 (i). {z } internalization of PDE Firm entry reduces incumbent firms size and profits, and hence decreases the repayments to bank i. Each bank i internalizes only the effects of the competition it funded, thus K t+1 (i) multiplies the profit destruction externality, d(nt+1) N t+1 N t+1 K. First order condition with respect to k t+1(i) t(i) defines a firm entry condition, which holds as long as the number of entrants, k t (i), is positive. Entry occurs until ex ante firm value, q t (i), is equalized with the expected, discounted entry cost, which is given by the deposit principal and the interest to be paid back next period, t +1, q t (i) =β µ (1 + rt ) (1 δ) " µct+1 # γ w t E t. (10) Z t C t 27 Bilbiie et al (2006) work with post entry value of firm, in their notation v t, whereas here q t is ex ante entry value of firms. Assuming the profit destruction externality away, the firm values are related by q t = v t /(1 δ). 11

12 The cost of creating a firm to be repaid at t +1isknownwithcertaintyasofperiodt. As there is no difference between marginal and average q t, firm entry drives down not only the value of entering firms, but also the value of incumbents until all firms value is equalized with the sunk entry cost. Since all banks are identical and there are no idiosyncratic shocks, one can impose symmetry to obtain the Nash equilibrium. The equation for firm value, q t, becomes: 28 q t = βe t " µct+1 C t γ µµ 1 1 # d t+1 +(1 δ)q t+1. (11) H The parameter H plays in bank market the same role that θ plays in goods market. At one extreme, H =1or absolute bank monopoly, equation (11) says that there is no entry as there is no marginal (and average) return from funding an entrant: the portfolio expansion effect is totally offset by profit destruction effect. 29 The economy is starved of firm entry and of any activity as well. The model displays a gradual reduction in market power as the number of banks, H, increases. 30 At the other extreme, H =, the equation simplifies to the usual asset pricing equation. 2.4 Aggregation and data consistent variables Aggregating the budget constraint across households, and noting that the share holdings in the bank mutual fund add up to one in equilibrium, yields the aggregate accounting constraint: C t + B t = d t N t + w t L, (12) where L is the aggregate labor supply, L = R l(j)dj. The aggregate accounting constraint states that j current consumption and deposits must be equal to total income, that is, labor income plus dividend income. Current household deposits are the measure of current real investment in the economy. Deposit 28 Recall that q t (i) is ex ante entry value of firm, hence the h entry entry loan repayment, i d t (i), is not multiplied by (1 δ). 29 Under H =1, equation (11) becomes q t = β(1 δ)e t (C t+1 /C t) γ q t+1, which is a contraction mapping because of discounting, and by forward iteration under the assumption lim T (β(1 δ)) T E t q t+t =0(there is a zero value of firms when reaching the terminal period), the only stable solution for firm value is q t =0, which implies N t =0. An alternative would be to assume that the monopolist bank takes into account its influence on the aggregate consumption demand, C t. This channel is reminiscent of Ford effect described in d Aspremont et al (1996) where a firm-monopolist, owned by households, internalizes the effects of dividend pay outs, that boost households income, on demand for its output. In an alternative multi-location setup, where firms compete in a national market rather than in local markets, there is firm entry under H =1at each location as long as there is more than one location in the economy. 30 In Salop s (1979) model of competition on a circle, the addition of one establishment makes all establishment more substitutable with each other, so markups fall. The same is true for conventional models of Cournot competition. 12

13 market clearing equates deposits with investment in new firms: B t = w t Z t n t. (13) Labor market equilibrium requires that the total amount of labor employed in the production of goods and in creation of new firms must be equal to the aggregate labor supply: L = C t Z t (N t ) 1 θ Z t n t. As in Bilbiie et al (2006), although the labor supply is fixed, there are labor market dynamics, as labor reallocates between the two sectors of the economy in response to shocks. The allocation is determined by banks deciding on firm entry. Thus, the value of a firmtoabank,q t, plays a central role in determining the labor allocation. 31 Although the model does not feature an explicit interest rate markup over the deposit interest rate, one may define an aggregate ex post markup in banking, µ B t, as the residual concept: µ B t = d tn t q t N t+1 r t. The modelling strategy of entry loan repayments makes it possible to treat firms of different vintages symmetrically. There is also no difference between marginal and average q t. Takingintoaccountthe time-to-build lag between the period of a firm entry and the period it starts repaying the entry loan, one can think of the ratio d t N t /q t N t+1 as measuring the relative return from funding a marginal (and average) firm. As argued in Ghironi and Melitz (2005), when investigating the properties of the model with endogenous variety in relation to the data, any variable in units of the consumption basket should be deflated by a data consistent price index. In the model, the average variety price, p t,isclosertoactualcpidata than the welfare-based price index, P t. Therefore, data consistent counterparts of the model variables are obtained as follows: Xt R = P t X t = X t X t =. p t ρ t N 1/(θ 1) t 31 To close the model, either the aggregate accounting constraint or the labor market clearing condition is necessary. 13

14 For example, the expenditure definition of GDP is Y t = C t + B t. Then, GDP in data consistent terms is Y R t = C R t + B R t = y t N t + n t µ F, (14) where C R t is aggregate consumption and is given by the product of firm level output, y t and the mass of producing firms in period t, N t ;andb R t is the amount invested in firm creation evaluated at average prices and is given by n t /µ F. Table 8 in Appendix summarizes the model equations. The model constitutes of a system of 11 equations in 11 endogenous variables. 32 Of these endogenous variables, the mass of firms, N t, is predetermined as of time t. The exogenous state variable is the aggregate productivity, Z t. My benchmark model under perfectly competitive banking nests Bilbiie et al (2006) with inelastic labor supply and Dixit-Stiglitz preferences, notwithstanding the timing discrepancy in firm entry equation (10). 3 Results 3.1 Calibration I interpret model periods as quarters. Table 1 shows the calibrated parameter values. For computation of second moments, I set the parameter H before deregulation such that it implies a bank markup of about 10 percentage points, then the roughly 34% increase in the mass of firms pins down H after deregulation. The discount factor and the inverse of intertemporal elasticity of substitution are set at standard values for RBC literature. Although it implies a fairly high firm markup, I set the elasticity of substitution across goods (θ) at 3.8 for two reasons. First, it fits U.S. plant and macro trade data. 33 Second, the model, void of period by period fixed cost, delivers equal marginal and average cost. Therefore the firm markup, µ F,isameasure of both markup over marginal and average cost. 34 Steady state levels of variables are denoted by dropping the time subscript. All exogenous variables, including aggregate productivity, are constant in steady state. I set steady-state aggregate productivity, 32 The model can be reduced to a system of 3 equations in 3 variables: the number of firms, N t, aggregate consumption, C t, and aggregate productivity, Z t. 33 See Bernard et al (2003) and Ghironi and Melitz (2005). 34 In Bilbiie et al (2006) free entry ensures that firms earn zero profits net of the entry cost, meaning that firms price at average cost inclusive of the entry cost. In my model, with rationed entry under monopolistic banks, firms price at average cost partly inclusive of the entry cost. 14

15 Z, and aggregate labor endowment, L equal to one without loss of generality. These parameters determine the size of economy, but leave the model second moments, unaffected. Table 1: Quarterly calibration Preferences Economy scale Exogenous process Discount factor β 0.99 Agg. productivity Z 1 Prob. of exog. exit δ Elast. of goods subst. θ 3.8 Aggregate labor L 1 Agg. prod. persist. ψ Z 0.90 Risk aversion γ 1 Ghironi and Melitz (2005) set the size of the exogenous firm exit shock δ =0.025 to match the U.S. empirical level of 10% job destruction per year. 35 Using as a guideline the fraction of firm closures and bankruptcies over the total number of firms, reported by the U.S. Small Business Administration, consistently around 10% per year over the recent years, gives the same calibration. 36 In contrast to a model without entry, the dynamics of firm entry results in responses of aggregate variables to temporary exogenous shocks that persist beyond the duration of the shocks. I set the persistence of the aggregate productivity process to As such, I do not attempt to replicate exactly U.S. data moments. I illustrate the implications of bank monopoly power for firm and aggregate volatility by computing changes in second moments induced by deregulation for the standard deviation of productivity innovations of 1%. 3.2 Steady state All endogenous variables are constant in steady state. The steady state interest rate is pinned down as usual by the rate of time preference, 1+r = β The closed form solution for the steady state mass 35 Empirically, job destruction is induced by both firm exit and contraction. In the model the exogenous exit shock induces firm exit. 36 There are two calibration approaches that might suggest an upward revision of the δ calibration. First, one might interpret δ as a parameter controlling the fraction of non-performing loans. Then the average delinquency rate for commercial and industrial loans between 1986 and 2006 is 3.34% per quarter (FDIC Charge-off and Delinquency Rates data). Second, one might look at the survival rates for new firms. Two-thirds (66%) of new employer establishments survive at least two years, and 44% survive at least four years (Knaup, 2005). Assuming that the number of years that a firm survives follows geometric distribution with parameter δ, one can calibrate δ at per quarter. In general, higher δ results in a lower number of firms in steady state and lower persistence of endogenous variables. Setting δ =0.025 implying expected firm lifetime of 10 years adjusts for the fact that larger firms tend to survive longer. Since the model here features no firm heterogeneity, the parameter δ might be thought of as an output weighted probability of exit, making a plausible choice. 37 The structure of models with varying product space calls for corrections to the standard formula for of Solow residual in order to estimate a model consistent productivity process. See Bilbiie et al (2006). For example, Devereux et al (1996) estimate the persistence parameter of 0.91 for their model with firm entry. 38 As in typical DSGE models, the interest rate is pinned down by household time preference, which is kept constant across simulations. In the data, however, the deposit interest rate increased after the deregulation. Thus, in the model the 15

16 of firms, N, is N = β(1 δ)(1 1/H) ZL. (15) (θ 1)(1 β(1 δ)) + δβ(1 1/H) Given the solution for N it is easy to recover solutions for all other variables. The number of new entrants makes up for the exogenous destruction of existing firms, n = δ/(1 δ)n. From equation (15) it is clear why steady state aggregate productivity, Z, orthelaborendowment, L, function as scale parameters. Figure 2 shows how key variables depend on H given the model calibration described above. Although some of the model s dynamic equations are different, my model nests the steady state solution of Bilbiie et al (2006) with inelastic labor supply as H. That is, the model nests the market outcome in the economy with perfectly competitive banking and carries over the properties of Bilbiie et al s steady state. An increase in long-run aggregate productivity results in a larger number of firms, higher consumption and firm value. The mass of firms, N, tendstozeroifθ tends to infinity or if H tends to one. For banks to find it profitable to let firms enter, the expected present discounted value of the future profit stream must be positive, so as to cover the sunk entry cost. But profits tend to zero in all periods if firms have no monopoly power. Marginal (and average) return from firm creation also tends to zero if H tends to one as the portfolio expansion effect is totally offset by the profit destructioneffect. Increasing H from one shows that the portfolio expansion effect dominates the profit destructioneffect up to H marginally below 2, and the dominance reverses from thereon. 39 The interplay of these effects causes the mass of firms in bank s portfolio (K) to be a non-monotonic function of H. Nevertheless, the mass of firms in the economy, N, is a monotonic function of H. 40 Firm size, measured by either firm output (y) orfirm level employment (l), and profit (d) are monotonically decreasing functions of H. As H increases, the mass of firms in the economy increases, eroding each firm s market share and hence profit. A decline in bank market power results in more entrants, and hence in an increase in share of investment in aggregate output, captured by the ratio B/Y. Bank market power results in low firm valuation (q) due to internalization of the profit destruction change in bank markup after the deregulation stems only from a decrease in loan price, d/q. 39 The inflection point for this particular calibration is H = TheincreaseinN induced by a fall in bank monopoly power is welfare improving as it allows households to enjoy more variety and higher consumption. In a version of this model with elastic labor supply, the increase in N leads to both higher consumption and labor effort, with the welfare gain of the former dominating the disutility from extra labor. 16

17 externality. The bank return on firm creation (that might be thought of as the loan price) is d q = r + δ 1 1/H, which captures a premium for expected firm destruction (δ) andtheeffect of bank market power. Hence, the steady-state banking markup, µ B = d/q r, approaches δ as H. The banking markup diverges to infinity as H 1. The steady-state predictions of the model are consistent with empirical findings that associate more vigorous banking competition with a greater number of establishments and a smaller establishment size. 3.3 Impulse responses Impulse responses highlight the difference between monopolistic and competitive banking in the model s dynamics. Figure 3 shows the responses, in percent deviations from steady state to a 1% increase in aggregate productivity with persistence 0.9 under monopolistic banking (where H = 1.5) and competitive banking (where H is set to a sufficiently high number, H = 2000). The model is stationary under temporary shocks. The number of quarters after the shock is on the horizontal axis. Variables with the superscript R denote variables in data consistent terms. 41 The following applies to both scenarios. The aggregate productivity shock makes the business environment more attractive, drawing a higher mass of entrants than in steady state. This translates into a temporary larger mass of producers with a lag, due to the sunk entry cost and the time to build lag. This induces marginal cost and the relative price of each product, ρ, to start increasing only in the period after the shock, when a larger number of producing firms puts pressure on labor demand. Consumption and GDP, both in data consistent terms, also increase. As in the data the aggregate ex post bank markup is countercyclical. All variables return to the respective steady states in the long run. The responses of firm level output, y, and aggregate output in data consistent terms, Y R, underline the different roles of intensive and extensive margins during expansions. The model predicts that the expansionary effect of higher productivity takes place initially through the intensive margin. Output per firm rises, because the aggregate consumption demand is higher and the predetermined number of producers remains constant on shock impact and then increases slowly. Over time, the increase in ρ t 41 I show impulse responses of data consistent variables to maintain continuity between this section and the following section where I compute second moments. The impulse responses of welfare consistent variables are qualitatively similar. 17

18 Figure 2: The dependence of endogenous variables on H in the steady state. Figure 3: Impulse responses (in percent deviations from steady state) to a 1% aggregate productivity shock under monopolistic and competitive banking. 18

19 pushes firm level output below the steady state level, but the aggregate expansion continues through the extensive margin, as the mass of producing firms increases. Noteworthy, firm-level output is actually below the steady-state level during most of the transition, except for a short lived initial expansion. These predictions are the same as in Bilbiie et al (2006). During the business cycle, there is a reallocation of the fixed labor supply from production of consumption goods to creation of new firms. The increase in productivity makes some labor redundant in production of goods (as aggregate consumption demand rises by less than income due to consumption smoothing) and at the same time boosts entry, as firm profits are higher and the cost of creating new firms is lower. Over time, the rising cost of effective labor and hence the rising burden of sunk entry cost redistributes labor back to production of consumption goods. In contrast to a model without entry, the dynamics of firm entry result in responses of aggregate variables that persist beyond the duration of the exogenous shock. Turningtothedifferences in responses across banking scenarios, the effects of an aggregate productivity shock are amplified in the monopolistic banking economy. Combining the aggregate accounting constraint (12) with goods pricing (5) and deposit market clearing (13) all linearized one obtains, 1 C µ F C B b t 1 C N θ B b t + bn t = ZL Z n b t, where percentage deviations from steady state are denoted by variables with hats. All variables on the left-hand side are endogenous. In particular, Nt b is the endogenous state that does not respond to period t shocks. The ratio on the right-hand side, ZL/n, is larger under monopolistic banking. The exogenous scale parameters, Z and L, are the same for both scenarios. However, monopolistic banks suppress the mass of firms, N, and hence firm entry, n, is lower in steady state. Sustaining this lower mass of large and profitable firms requires less resources than under competitive banking. The aggregate productivity shock then generates much stronger wealth effect that causes a more pronounced boom in consumption, hence goods production, and investment in new firms. 42 This stronger consumption boom then raises significantly firm-level output and profits. However, the expansion along the intensive margin is short- 42 Firm monopoly power and variety as such are not crucial for this mechanism. For example, in a model with decreasing returns to labor in production of homogenous goods, firms earn profits as well, hence making firm entry possible. In this model the implications of monopolistic banking will be the same as in the benchmark model. See Stebunovs (2007) for details. 19

20 lived. The incentive to create a large mass of new firms is similarly short-lived, as profit opportunities are exhausted quickly. The influx of new firms drives firm level output below the steady state in just a few periods. The short-lived firm investment boom makes firm entry more volatile, which in turn makes firmlevel output more volatile as well. After over 20 quarters, the effects of monopolistic banking vanish and the impulse responses in the monopolistic and competitive banking economies converge. In the bigger, competitive banking economy there are more firms and less steady-state profits per firm. An aggregate productivity shock of the same magnitude does not generate such a strong wealth effect and consumption investmentboom, leadingtolowerfirm entry and output volatility. Interestingly, the response of GDP in data consistent terms, Y R, is not significantly amplified before the deregulation. The following section considers this issue in detail. 3.4 Second moments In this section I compute changes in model second moments induced by changes in H, thatis,before and after the financial deregulation, keeping other model parameters and the stochastic shock process the same. The standard deviation of productivity innovations is 1%. I calibrate H as follows. I pick the value of H before financial deregulation that implies a bank markup of about 10 percentage points. 43 Then the roughly 34% increase in the mass of firmspinsdownthevalueofh after deregulation. The resulting H before deregulation is equal to about 1.48, after deregulation H is about Table 2 shows model second moments under both banking scenarios scaled by standard deviation of aggregate productivity, σ Z = The reduction in bank monopoly power generates significant declines in volatility of firm entry, firm output, data consistent consumption, and data consistent investment. The model generates firm-level decrease in volatility similar to the data. 46 Davis et al (2006) report two measures of firm volatility. In the spirit of my model, one might consider the measure that takes into account firm dynamics and hence rely on the 18% decline in firm level volatility between 1980 and 2000 as a benchmark. 47 Table 7 in Appendix shows the changes in empirical moments of aggregate 43 In the aggregate data, the bank spread in 1980 was around 8 percentage points and in 2000 about 5 percentage points (see the details in Appendix). The model requires rather strong bank monopoly power to generate large volatility declines. 44 The implied bank markup before deregulation is 9.8 percentage points and after deregulation 6.81 percentage points. 45 The theoretical moments are HP filtered with λ = The model underestimates the decline in firm volatility in comparison with Davis et al (2006) as they calculate growth rates that are symmetric around zero and bounded. They report the volatility of firm growth rate calculated as γ t =(x t x t 1 )/(x t + x t 1 )/2, wherex is some firm size measure. 47 As dictated by data availability Davis et al estimate firm volatility based on firm employment. The preferred measure of firm volatility here is based on firm output because its contribution to GDP is immediately clear from equation (14). In the model, firm-level labor and output always move in the same direction. However, the magnitudes of movements might 20