# Credit Growth and Capital Requirements: Binding or Not?

Claire Labonne, Gildas Lamé

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Direction des Études et Synthèses Économiques

G 2014 / 07

Credit Growth and Capital Requirements:
Binding or Not?

Claire LABONNE et Gildas LAMÉ

Document de travail
INSTITUT NATIONAL DE LA STATISTIQUE ET DES ÉTUDES ÉCONOMIQUES

Série des documents de travail
de la Direction des Études et Synthèses Économiques

G 2014 / 07

Credit Growth and Capital Requirements:
Binding or Not?

Claire LABONNE* et Gildas LAMÉ**

JUILLET 2014

Les auteurs remercient Jean-Baptiste BERNARD, Guillaume CLÉAUD et Jean-Baptiste HAQUIN pour leur soutien technique et Farida AZZI pour son excellente assistance. Nous remercions aussi José BARDAJI, François-Daniel CASTELLANI, Éric DUBOIS, Henri FRAISSE, Mathias LÉ, Matthieu LEQUIEN, Jean-Stéphane MÉSONNIER, Henri PAGÈS, Aurélien POISSONNIER, Corinne PROST et Jan RIEPE pour leurs commentaires. Nous voudrions tout particulièrement remercier Vincent BOUVATIER et Andrea NOBILI pour leurs riches discussions.

<footnote>* Autorité de contrôle prudentiel et de résolution (ACPR), 61 rue Taitbout, 75009 PARIS. The views expressed in this paper do not necessarily reflect those ACPR.</footnote>

<footnote>** Département des Études Économiques - Division « Études Macroéconomiques» Timbre G220 - 15, bd Gabriel Péri - BP 100 - 92244 MALAKOFF CEDEX</footnote>
# Credit Growth and Capital Requirements: Binding or Not?

## Abstract

This paper examines the sensitivity of non-financial corporate lending to banks' capital ratio and their supervisory capital requirements. We use a unique database for the French banking sector between 2003 and 2011 combining confidential bank-level Bank Lending Survey answers with the discretionary capital requirements set by the supervisory authority. We find that on average, more capital means an acceleration of credit. But the elasticity of lending to capital depends on the intensity of the supervisory capital constraint. More supervisory capital-constrained banks tend to have a credit growth that is less sensitive to the capital ratio. Our results also show a similar effect for non-performing loans. When banks are constrained, credit growth is all the more sensitive to this type of assets as their share rises. However, both aforementioned effects weaken close to the supervisory minimum capital requirement.

**Keywords:** Bank Lending, Bank Regulation, Capital

## Crédit et capital réglementaire : l'exigence est-elle contraignante ?

## Résumé

Ce papier étudie la sensibilité de l'octroi de crédit aux SNF au ratio de capital des banques ainsi qu'aux contraintes en capital imposées par leur superviseur. Nous utilisons une base de données unique sur le secteur bancaire français combinant les réponses individuelles au *Bank Lending Survey* avec les exigences discrétionnaires en capital fixées par le superviseur. Nos résultats indiquent qu'en moyenne, plus de capital conduit à une accélération du crédit. Mais l'élasticité de l'octroi de crédit au capital dépend de l'intensité de la contrainte du superviseur. La dynamique du crédit est moins sensible au capital pour les banques qui font face à des contraintes en capital. Nos résultats montrent par ailleurs que le ratio de créances douteuses a un effet de même nature. En effet, la sensibilité du crédit à ce type d'actifs est d'autant plus forte que les banques en détiennent une large part et sont contraintes. Cependant, ces effets se dissipent lorsque la situation des banques est proche du minimum réglementaire.

**Mots-clés** : Crédit bancaire, Réglementation bancaire, Capital

**Classification JEL** : G21, G28, G32
# 1 Introduction

80% of non-financial corporations (NFCs) funding depends on banks in France, to be compared with only a third for the United States (Paris Eurolace (2013)), which explains why banks are a crucial element for French firms to make the investments essential to their businesses. The health of the banking sector has been and is under close scrutiny, as exemplified by the Asset Quality Review the European Central Bank and national supervisory authorities are undertaking in 2014.

The evolution of banking regulation spurred by the Third Basel Accord in 2011 and its trans-
position into European and French law in 2013 triggered a debate over the impact on the real
economy. The main policy instrument in the supervisory toolbox is capital ratios. The amount
and quality of capital required for micro-prudential purposes has been increased through core eq-
uity Tier 1 ratios or the capital conservation buffer for example. Macro-prudential requirements,
such as the countercyclical capital buffer, G-SIFIs requirements or the systemic risk buffer even
increase the weight of the supervisory constraints.

If banks have to fulfill these capital requirements and manage their balance-sheet accordingly, this could induce them to reshuffle their investments. Some market segments could be privileged over others, depending on their capital costs. The central question of the current debate is then: how do banks adjust their lending in response to fluctuations in their capital-to-assets ratios? The answer to the question is not straightforward. The elasticity of lending to capital depends on capital costs relative to other sources of funding as well as investor's risk aversions or their returns expectations (see Admati and Hellwig (2013)).

We propose to participate to this debate by making use of a unique database for the French banking sector between 2003 and 2011 combining bank-level Bank Lending Survey (BLS henceforth) answers with the discretionary capital requirements set by the French Prudential Supervisory and Resolution Authority. Thanks to this database, we can estimate the impact of additional capital (measured by the bank's Tier 1 capital-to-assets ratio) on quarterly credit growth and qualify it with respect to the intensity of the supervisory capital constraint.

We find that on average, in our sample of French banks, more capital means an acceleration of credit. But the elasticity of lending to capital depends on the intensity of the supervisory capital constraint. More supervisory capital-constrained banks' credit growth tend to be less responsive to a higher capital ratio than unconstrained banks. We thus show that making the supervisory constraint bind induces banks to slow their production of loans. We also find that more supervisory capital-constrained banks tend to be more reactive to the ratio of non-performing loans than unconstrained banks. The former are more prone to reduce credit allocation after a rise in these problematic assets than the latter. However, both aforementioned non-linear effects seem to weaken as banks get close or below their supervisory minimum capital requirement.

The remainder of the paper is organized as follows. The next section briefly reviews the literature related to our analysis. Section 3 presents a summary of the theory surrounding bank capital and lending. Section 4 takes a look at the data used, which comprise detailed bank-level BLS survey responses as well as individual fine-tuned capital requirements set by the banking supervisor in France. In section 5, we outline our methodology for estimating the link between banks' capital ratio and lending. Section 6 reports our empirical findings and section 7 concludes.
# 2 Related literature

The literature has been intensively examining the effects of capital on lending since the first regulations were defined with Basel I in 1988. But the question has never been under such spotlight before the financial crisis triggered a worldwide regulatory response. From an empirical perspective, the literature has tackled three essential issues. First of all, uncovering the potential effect of capital requires disentangling supply effects from demand effects on bank lending. Secondly, a clear distinction must be made between the various possible capital ratios (regulatory ratio or non-weighted, absolute level or relative level compared to a target for example). Thirdly, the relationship between bank lending and capital might not be linear. In this section, we review these essential issues for our question.

## 2.1 Disentangling loan supply from loan demand

The most problematic issue for isolating the effect of capital on lending is to control for changes in loan demand. Several approaches have been used in the literature, the most common one being to explicitly take into account economic conditions directly linked to loan demand such as GDP growth or similar macroeconomic variables (see for example Gambacorta and Mistrulli (2004) or Berrospide and Edge (2010)). Other papers use regional variations of bank health and economic conditions to disentangle supply from demand effects. Bernanke et al. (1991) use simple reduced-form loan equations to detect the effect of capital on lending during the credit crunch that took place in New England in 1990. A third solution consists in taking advantage of a natural event that resulted in a shock to banks’ capital base without any changes in loan demand. These studies typically focus on multinational banking groups which go through a shock to one of its foreign branches (such in Peek and Rosengren (2000)) and see how the supply shock in the foreign country affect lending in the home country of the bank.

Finally, several papers tackle the disentangling issue with questions extracted from national bank lending surveys. In the case of the US Senior Loan Officer Opinion Survey (SLOOS), several papers use the aggregated responses of banks on their standards to study the effect of credit supply on the fluctuations of the US economy such as Lown et al. (2000), Lown and Morgan (2006) and Ciccarelli et al. (2010) among others. Most of them build on standard monetary VARs that include these survey responses to better control for supply-side effects but they do not explicitly focus on the impact of bank capital. The Eurozone, with its own Bank Lending Survey (BLS) which started in 2002Q4, also contributes to the literature. Works that make use of the aggregate survey data circumvent the limited size of the sample by working on area-wide panels such as Ciccarelli et al. (2010) or Hempell and Sørensen (2010). In the literature, only a few papers have taken advantage of the bank-level BLS data. Blaes (2011), Del Giovane et al. (2011) and Bassett et al. (2014) for instance all use bank-level credit data combined with individual responses to the lending survey to study the dynamics of credit in Germany, Italy and the US respectively. So far, the literature has revealed the significant contribution of these bank lending surveys to identify credit supply shocks especially during the financial crisis. For example, Del Giovane et al. (2011) find that supply factors such as banks’ balance sheet position or their perception of credit risk had a significant contribution though relatively minor on the fall of bank lending in Italy during the 2007-2009 financial crisis.
## 2.2 Observed capital ratios and regulatory capital requirements

In general, one would presume that the minimum capital requirements affect banks' observed capital ratios and subsequently lending. This issue has been studied in the past in the regulation impact analysis literature. Aiyar et al. (2014) test if changes in capital requirements affect loan supply by regulated banks and whether unregulated substitute sources of credit are able to offset changes in credit supply by affected banks. They use time-varying bank-specific minimum capital requirements imposed by UK regulators. They find that regulated banks decrease lending in response to tighter capital requirements on a relevant reference group of regulated banks. Francis and Osborne (2012) find that capital requirements affect banks' desired capital ratio. They show that the potential gap between the actual and desired ratio have significant consequences on bank lending. More recently, Brun et al. (2013) analyze the consequences of capital requirements on bank lending using loan-level data and the transition from Basel I to Basel II. They find a strong negative effect of capital requirements on lending.

Some papers also focused on observed capital ratios and find a positive relationship between capital and lending. Berrospide and Edge (2010), Carlson et al. (2013) among others use bank-level data to estimate the impact of capital on lending and find small positive effects on credit dynamics (see table 1 for more detailed quantitative results on the impact of bank capital fluctuations on lending). The qualitative side of these results are in line with the theoretical features uncovered by Repullo and Suarez (2013) who show banks under any regulatory regimes will still hold positive capital buffer in order to preserve their future lending capacity. However, the elasticity found in the literature greatly varies as showed in table 1. This heterogeneity could come from non-linear effects between capital and lending.

<table><caption>Table 1: Estimations of the impact of observed capital ratio on lending growth</caption><thead><tr><td>Paper</td><td>Effect of a 1-ppt shock to:</td><td>Dependent variable</td><td>Impact (ppt)</td></tr></thead><tbody><tr><td>Bernanke and Lown (1991)</td><td>Bank capital ratio</td><td>Bank lending growth (US)</td><td>+2.3</td></tr><tr><td>Berrospide and Edge (2010)</td><td>Bank capital-to-assets ratio</td><td>BHC loan growth (US)</td><td>+0.145</td></tr><tr><td>Carlsson et al (2013)</td><td>Total capital-to-assets ratio</td><td>Bank lending growth (US)</td><td>+0.13-2</td></tr><tr><td>Francis and Osborne (2012)</td><td>Surplus bank capital ratio</td><td>Bank lending growth (real sector UK)</td><td>+0.060</td></tr><tr><td>Gambacorta and Mistrulli (2004)</td><td>Excess regulatory capital-to-assets ratio</td><td>Bank and credit cooperatives lending growth (Italy)</td><td>+0.744</td></tr></tbody></table>

## 2.3 Non-linear effects between capital and lending

The link between capital and lending seems to be non-linear according to recent empirical research. Jiménez et al. (2012) find highly capitalized banks are less prone to lend to new borrowers but the sign is reversed if interactions with macroeconomic variables are considered in the regression. Carlson et al. (2013) show the capital ratio has a more significant impact on lending when it is already low than when it is high. The significance also depends on the type of loans considered. These results corroborate those found by Albertazzi and Marchetti (2010) in the case of Italy during the 2008-2009 financial crisis. Only very low-capitalized banks (less than 10% RWA) cut lending; in addition apart from bank-specific factors, firm-specific characteristics (such as size, riskiness) are essential determinants too. In the same vein, di Patti et al. (2012) study the transmission of shocks to banks balance sheets to their loan portfolio. A deterioration of banks' capital position had a significant negative impact on lending during the Lehman crisis. They argue a higher capital ratio positively influences lending indirectly through its interaction with asset quality and the funding structure so that there's not a straight linear relationship between these two variables of interest.
# 3 Capital and Credit Supply: Insights from Theory

Why and how would equity capital (capital in general by extension) impact credit growth? It depends both on the rationale for holding capital and on capital market characteristics.

## 3.1 Economic and Regulatory Capital

Banks hold capital because either they think it is optimal (economic capital) or because super- visors or the market want them to do so (regulatory capital). Equity capital represents the part of unborrowed funds available for a bank that can be used to finance its investments. The amount of capital is determined by bankers under the framework of their portfolio management strategy. This 'voluntarily held' equity does not have an obvious impact on credit growth. Increasing equity in absolute terms allows the expansion of the balance sheet, so it can result in higher credit supply, ceteris paribus. If the banker increases its ratio of equity to assets, it may be to fit its funding mix to new asset classes, especially their liquidity and maturity characteristics. So it can be associated with an increase for some credit categories and a decrease for others.

When equity capital stems from the banker's optimization problem, its impact depends on the production function and risk aversion of the bank. But external constraints, due either to the supervisor or market forces, disrupts the asset allocation desired by the bank. If the capital level is not already high enough to fulfill the requirements, the bank has to raise equity. However, providing equity may be more costly than other forms of funding. As a consequence, banks would attempt to shrink the size of their balance sheet, hence the amount of assets and certainly credit if all asset classes are affected uniformly.

Thus, regulatory capital could shrink credit growth while economic capital has an uncertain effect on the latter. The size and direction of these effects depend on two conditions: the relevancy of the capital structure and the specificity of capital as a funding instrument (see table 2).

## 3.2 Modigliani-Miller Propositions

The Proposition I of Modigliani-Miller (M&M henceforth, Modigliani and Miller (1958)) states the irrelevance of the capital structure on the value of the firm and on its funding cost while Propo- sition II shows that equity cost rises with leverage. However, M&M has been a hotly-debated issue among academics and bankers alike on its application in the banking sector in contrast with other industries. If M&M applies in the case of banks, the share of equity in the funding mix should not be a source of concern for credit growth. Miller (1995) answers whether the M&M's propositions apply to banks and he replies with a very short abstract: "Yes and no.", thus emphasizing the complexity of the question.

Indeed, Proposition I theoretically holds with no taxation and no market imperfections. But banks' existence is the very result of information asymmetries (between the lender and the bor- rower) and they suffer themselves from agency issues (between the shareholder and the manager, see Dewatripont and Tirole (1994)). Moreover, deposit insurance and taxation also create dis- tortions. All these elements entail the failure of M&M's Proposition I about the irrelevancy of capital structure. In such situations, funding costs may then depend on the funding mix because tax rules that favor debt over equity prevail for example. When both propositions fail, a bank can leverage up without equity being more costly. In this case, switching to a higher share of equity
in the capital structure would deprive the bank of cheaper financing such as deposits or wholesale funding and it would most likely lead it to cut credit.

However, a more realistic framework would not necessarily entail the failure of Proposition II, which states that, with or without taxes, equity costs rise with leverage as risk in the bank would increase and investors would want to be adequately compensated for the riskiness of their potential investments in the bank.<fnref n="1" /> So raising the equity share of the capital structure would decrease its marginal cost, offsetting a part of the structural higher cost of equity financing. In such setting, the impact of more capital on credit is not clear-cut. Table 2 sums up the possible outcomes of a higher capital ratio on bank credit growth under different assumptions regarding the validity of M&M's propositions.

<table><caption>Table 2: Theoretical effect of a higher share of equity capital on lending</caption><thead><tr><th rowspan="2"></th><th colspan="2">M&M's Proposition II</th></tr><tr><th>Holds</th><th>Fails</th></tr></thead><tbody><tr><th>M&M's Proposition I :</th><td>Holds</td><td>Irrelevant</td></tr><tr><th></th><td>Fails</td><td>+/-</td></tr></tbody></table>

The paper tries to uncover the variations induced by the level of capital in general on lending growth while taking into account the binding or non-binding aspect of capital constraint.

# 4 Data

## 4.1 Balance-sheet data

We extract balance-sheet data from banks' quarterly reports to the French Prudential Supervisory and Resolution Authority. Overall, our sample represents around 64% of all bank assets (see appendix A.1). Table 3 shows some summary statistics of the explaining variables used in the sections of this paper. It shows that the average actual Tier 1 capital-to-assets ratio (CAT1) in our sample is quite high at 6%. The average ratio of non-performing loans (NPL) is low.

Our main variable of interest is credit granted to NFCs. More precisely, we consider the sum of every credit type granted to NFCs: liquidity, export, housing, commercial, equipment, account receivable. As it is usually done in the banking sector, only credit outstanding amounts are reported. Due to the length of loan contracts, the reported amounts can be the outcome of deals made many periods before. To remove part of this inertia and in order to get closer to new credit activity (which is believed to be influenced by banks' capital position), we actually consider the quarterly growth rate of credit granted to NFCs in the rest of our paper.<fnref n="2" /> According to table

<table><caption>Table 3: Summary statistics of bank variables. Outlier observations that do not correspond to mergers and acquisitions (M&A) operations are excluded.</caption><thead><tr><th></th><th>N</th><th>mean</th><th>sd</th><th>min</th><th>max</th></tr></thead><tbody><tr><th scope="row">QoQ_NFCloans</th><td>386</td><td>0.021</td><td>0.086</td><td>-0.378</td><td>0.651</td></tr><tr><th scope="row">CAT1</th><td>386</td><td>0.059</td><td>0.029</td><td>0.015</td><td>0.172</td></tr><tr><th scope="row">NPL</th><td>386</td><td>0.020</td><td>0.021</td><td>0.001</td><td>0.135</td></tr></tbody></table>

<footnote n="1">¹See Admati and Hellwig (2013) for a discussion.</footnote>

<footnote n="2">²We argue this approach allows to get closer to credit activity during the period observed, though it is still plagued by the well-known shortcoming that changes in loan stocks also reflect write-offs, exchange-rate effects, reporting changes etc.</footnote>
<figure><img src="image_2.png" /><figcaption>Figure 1: Quarterly growth of rate of loans to NFCs for our total sample (blue solid line), the aggregate French banking sector (red dotted line) and all credit institutions in France (pink dashed line).</figcaption></figure>

3. NFCs credit growth (QoQ_NFCloans) displays significant volatility across both the time and cross-sectional dimensions.

As shown in figure 1, NFCs credit growth has been quite dynamic in France for the past few years. It broadly accelerated until the crisis burst. After a peak at the end of 2007, credit growth began to significantly slow until contracting in the first half of 2009. Despite a short economic recovery following the trough in 2008-2009, NFCs credit dynamics became subdued again as the European sovereign debt crisis began to take hold in the core countries of the Euro area. Then, two years after the first credit crunch, we observe a contraction in loans granted to NFCs when problems in other parts of the Eurozone developed again. Regarding the representativeness of our sample (see section 4.2), notice that the aggregate credit dynamics of our sample closely follows the banking sector's as well as all credit institutions'.

## 4.2 Bank Lending Survey data

The European Central Bank has been conducting the Bank Lending Survey (BLS) since 2002Q4 actually.<fnref n="3" /> It consists in a set of questions with categorical answers filled every quarter by individual banks in the Euro area.<fnref n="4" /> The survey provides information on the supply and demand conditions they face, by loans and counterparty types. The banks' sample for each country is chosen by the national central bank to get representative information on developments in credit standards, non-interest rate credit conditions and terms, risk perception of banks and the willingness of banks to lend with both a backward- and forward-looking perspective. For our empirical assessment, we restrict the sample to a panel of 13 banks, queried in the survey from 2003Q1 to 2011Q4.<fnref n="5" />

Table 4 presents detailed statistics on the main responses on standards given by French banks

<footnote n="3">³The Bank Lending Survey sampling and time period coverage defines our own sample. We did not have access to the data corresponding to 2002Q4. The period 2003-2011 is characterized by both the transition from Basel I to Basel II and the crisis period. These structural breaks are tested in an econometric framework.</footnote>

<footnote n="4">⁴See Berg et al. (2005) for a complete description.</footnote>

<footnote n="5">⁵Three banks in our sample stopped being questioned a few quarters before 2011Q4 for the BLS.</footnote>
in the BLS. Similar to the features found in the BLS results for other Euro-area countries (Del Gio-
vane et al. (2011) for Italy or Blaes (2011) for Germany), French banks’ answers do not often differ
from the recurrent ”basically unchanged”. We also notice the fifth categorical response is almost
non-existent.

Figure 2a plots a balance of opinion on the question about the evolution of credit standards for the past quarter applied on loans to NFCs (computed as the sum of banks declaring to have tightened their standards minus the ones declaring to have eased). As shown in the figure, French banks tightened their credit standards to non-financial corporates three times in the past (2003, 2008-2009 and 2011H2). Turning to perceived credit demand by NFCs reported by French banks displayed in figure 3a, it seems to have continuously increased until Lehman bankruptcy. At the end of 2011, it appears that credit demand from NFCs was still weak compared to historical standards.

<figure><img src="image_3.png" /><figcaption>Figure 2: BLS questions on credit standards for France</figcaption></figure>

<figure><img src="image_4.png" /><figcaption>Figure 3: BLS questions on credit demand for France</figcaption></figure>
<table><caption>Table 4: Detailed statistics on the banks' responses to the general questions on credit standards and demand regarding loans to NFCs and mortgage loans. The number of responses per category is listed as well as their frequency.</caption><thead><tr><th>Responses<br>2003Q1-2011Q4</th><th>1="Tightened /<br>decreased considerably"</th><th>2="Tightened /<br>decreased somewhat"</th><th>3="Remained<br>basically unchanged"</th><th>4="Eased /<br>increased somewhat"</th><th>5="Eased /<br>increased considerably"</th><th>Total<br>observations</th></tr></thead><tbody><tr><td>NFCs credit standards</td><td>12<br>2.62%</td><td>50<br>10.92%</td><td>373<br>81.44%</td><td>23<br>5.02%</td><td>0<br>0%</td><td>458<br>100%</td></tr><tr><td>Mortgage credit standards</td><td>0<br>0%</td><td>19<br>4.15%</td><td>426<br>93.02%</td><td>13<br>2.84%</td><td>0<br>0%</td><td>458<br>100%</td></tr><tr><td>NFCs credit demand</td><td>9<br>1.97%</td><td>91<br>19.87%</td><td>322<br>70.30%</td><td>36<br>7.86%</td><td>0<br>0%</td><td>458<br>100%</td></tr><tr><td>Mortgage credit demand</td><td>13<br>2.84%</td><td>68<br>14.85%</td><td>263<br>57.43%</td><td>86<br>18.78%</td><td>28<br>6.11%</td><td>458<br>100%</td></tr></tbody></table>
<figure><img src="image_5.png" /><figcaption>Figure 4: Balance of opinions on the question of credit standards applied to loans to NFC during the past quarter.</figcaption></figure>

Figure 4 shows how the different underlying factors behind the change in credit standards for loans to NFCs varied over time.<fnref n="6" /> At first sight, the risk perception by French banks was the main reason that led them to tighten their standards for loans to NFCs in all these restrictive periods of credit distribution, though it is worth noticing that the cost of funds and balance-sheet constraints also impacted the banks’ decisions during the Great Recession and more recently in the midst of the European sovereign debt crisis.

Van der Veer and Hoeberichts (2013) warn about an issue about the survey data, namely whether respondents answer literally or not to the questions. The way we just interpreted the results of the survey implies banks do not literally respond to the BLS question but instead, report the "degree of tightness" at one point in time in the case of lending standards for example. The same would go for credit demand. As it is often done in the literature, we can construct the following BLS-related variables:

$$BLS\_S_{i,t} = \begin{cases} -1 & \text{if bank } i \text{ reported easing standards on loans to NFCs in quarter } t \\ 0 & \text{if bank } i \text{ reported no change in standards on loans to NFCs in quarter } t \\ 1 & \text{if bank } i \text{ reported tightening standards on loans to NFCs in quarter } t \end{cases}$$

$$BLS\_D_{i,t} = \begin{cases} -1 & \text{if bank } i \text{ reported decreased demand for loans to NFCs in quarter } t \\ 0 & \text{if bank } i \text{ reported no change in demand for loans to NFCs in quarter } t \\ 1 & \text{if bank } i \text{ reported increased demand for loans to NFCs in quarter } t \end{cases}$$

The balances of opinion presented in figure 2a and 3a are simply deduced from $BLS\_S_{i,t}$ and $BLS\_D_{i,t}$. Instead of using these two variables and by extension a simple balance of opinion,

<footnote n="6">⁶Cumulative net percentages for the underlying factors of bank credit standards represent for the determinant summarized as "Cost of funds and balance-sheet constraints" the sum of the net percentages for the factors "costs related to the bank's capital position", "bank's ability to access market financing" and "bank's liquidity position" for example.</footnote>
Van der Veer and Hoeberichts (2013) suggest to stick to the literal reading of the questions and construct cumulative BLS indicators, which are then supposed to reflect the "true" level of tightness of lending standards implied by the survey. These cumulative indicators are constructed as follows:

$$ Cumu\_BLS\_S_{i,t} = \begin{cases} 0 & \text{if } t = 2003Q1 \\ Cumu\_BLS\_S_{i,t-1} + 1 & \text{if } t > 2003Q1 \text{ and lending standards at } t \text{ are "tightened"} \\ Cumu\_BLS\_S_{i,t-1} + 0 & \text{if } t > 2003Q1 \text{ and lending standards at } t \text{ are "unchanged"} \\ Cumu\_BLS\_S_{i,t-1} - 1 & \text{if } t > 2003Q1 \text{ and lending standards at } t \text{ are "eased"} \end{cases} $$

$$ Cumu\_BLS\_D_{i,t} = \begin{cases} 0 & \text{if } t = 2003Q1 \\ Cumu\_BLS\_D_{i,t-1} + 1 & \text{if } t > 2003Q1 \text{ and credit demand at } t \text{ "increases"} \\ Cumu\_BLS\_D_{i,t-1} + 0 & \text{if } t > 2003Q1 \text{ and lending standards at } t \text{ is "unchanged"} \\ Cumu\_BLS\_D_{i,t-1} - 1 & \text{if } t > 2003Q1 \text{ and lending standards at } t \text{ "decreases"} \end{cases} $$

As shown in figure 2b, the "true" level of tightness in credit standards to NFCs has significantly increased, especially since the end of 2007. Notice that the pre-2007 period saw relaxed standards coinciding with growing credit distribution in France (see figure 1). After the peak of the financial crisis, conditions eased briefly before rekindling again with the European sovereign debt crisis. Turning to the credit demand by French NFCs, figure 3b points to a loan demand that has been decreasing ever since the inception of the survey. As expected, the financial crisis of 2008-2009 dealt a significant blow, pushing it to a new trough. The European sovereign debt crisis made the situation tense again at the end of our sample. Again, this evolution broadly concurs with NFCs credit dynamics (see figure 1). Overall, the message carried by the cumulative indicators is slightly different from the one presented in figure 2a and 3a but both are informative and relevant in the assessment of the credit market.

Van der Veer and Hoeberichts (2013) argue the cumulative indicators are better determinants of bank credit dynamics. From a practical viewpoint, Cumu\_BLS\_S_{i,t} (Cumu\_BLS\_D_{i,t} respectively) has the advantage of being non-categorical, in contrast with BLS\_S_{i,t} (BLS\_D_{i,t} respectively) which might lead to less precise estimates of the coefficients given the small size of our sample. They find for the Netherlands an economically significant negative effect of the level of standards on credit growth. Del Giovane et al. (2011) in the case of Italian banks test both the standard and cumulated indicators and conclude the former is more relevant in explaining credit dynamics. Given the negative dynamics of Cumu\_BLS\_D_{i,t} and the positive one of bank credit over most of the sample period in France, using Cumu\_BLS\_D_{i,t} might lead us to the wrong conclusion that demand is negatively correlated with credit growth for example. This apparently suggests that the banks' assessments on demand should be interpreted in terms of "acceleration" and "deceleration", rather than "increase" and "decrease". Thus, from now on, we will instead only consider BLS\_S_{i,t} and BLS\_D_{i,t} in the rest of the paper.

## 4.3 Capital requirements

Pillar I of the Basel II accord requires banks to maintain at all times a minimum of Tier 1 capital equal to 4% of risk-weighted assets (RWA). The second Pillar provides a framework for the supervisor to determine the soundness of a bank. Based on a thorough assessment of the institution's activities and risk profile, the supervisor can require the bank to hold a higher level
of capital than the minimum legal requirement of Pillar I. This additional buffer, determined each year at the French banking supervisor's discretion, constitutes the key variable of interest in our paper. Notice that the French banking supervisor has been making use of this strategy well before the official implementation of Basel II in France.

The average total regulatory requirement (regarding Tier 1 capital) between 2003 and 2012 for our banks sample has been above the legal minimum of 4%. For the period 2003-2006, the additional requirement was more or less stable. It increased during the following years until reaching in 2010 a peak. These supervisory requirements vary in the cross-sectional dimension but vary only gradually through time for a given bank.

The difference between the observed ratio and individual total discretionary requirements<fnref n="7" /> is on average strictly positive. Actually, some banks even have an effective solvency ratio way above the supervisor's requirement. Since 2009, whereas supervisory requirements are increasing, buffers are on average bigger than their beginning of period level. This may denote market discipline pressure.

For the sample gathered here, banks with a solvency ratio below the supervisory requirement are an exception. Concluding that the supervisor has no efficient pressure here on banks would be missing the point. Such a strict definition does not account for potential anticipations. Repullo and Suarez (2013) show that banks may even prefer benefit from a buffer above regulatory requirements so as to be able to lend as much as desired in the subsequent periods. Maintaining a buffer just enough to be above the supervisor's requirement might reflect continuous supervisor's pressure as well as the bank's internally desired path of conduct.

## 4.4 Macroeconomic data

To take into account aggregate demand, we consider the quarterly growth of nominal investment by NFCs (d_Investment). Eonia will be considered to control for monetary policy.

# 5 Methodology

## 5.1 Reduced Form Equation

We want to estimate the impact of a variation in the capital ratio on the growth rate of NFCs loans. Ideally, we would estimate a credit supply equation. However, we cannot ignore the simultaneity bias the estimation would suffer from. Therefore, we turn to the BLS survey to find a demand shifter and introduce a reduced form equation in which the parameter of interest is the coefficient $\beta$ that follows:

$$ \Delta y_{i,t} = \alpha + \beta(L)CAT1_{i,t} + \gamma(L)X_{i,t} + \mu_i + \lambda_t + q_t + \varepsilon_{i,t} $$

$\Delta y_{i,t}$ denotes the quarterly growth rate of credit to NFCs granted by bank $i$ between quarter $t$ and $t-1$. The variable is the sum of every credit type granted to NFCs: liquidity, export, housing, commercial, equipment, account receivable.

<footnote n="7">⁷Here, we consider as capital buffer the difference between economic capital and the supervisor requirement. This is not the difference between economic capital at date $t$ and the bank internal target capital, as tackled in dynamic capital ratio models (see Francis and Osborne (2012) for an example).</footnote>
We consider the prudential definition of funds for solvency purposes. The variable of interest is the amount of eligible Tier 1 Capital (namely "original own funds"). This is the sum of eligible capital, eligible reserves and funds for general banking risks.<fnref n="8" /> CAT1 is the ratio of this quantity to total assets.<fnref n="9" /> To correct for the endogeneity bias due to accounting relationships between the asset and the liability sides of the balance sheet, we consider the first lag of CAT1.<fnref n="10" />

$X_{i,t}$ denotes a set of control variables. At the bank level, we include the BLS categorical variables about credit standards ($BLS-S_{i,t}$) and demand ($BLS-D_{i,t}$). Non-performing loans ($NPL$) are also included to control for bank risk. At the macroeconomic level, we control for economic activity with NFCs quarterly nominal investment growth ($d\_Investment$) and monetary policy (Eonia). $\lambda_t$ is a time dummy, $q_t$ a seasonal dummy and $\mu_i$ a bank fixed effect.

## 5.2 Capital and Capital Requirements

In order to test for the non-linearity induced by supervisory capital requirements in the relationship between capital and credit growth, we use the following variable:

$$Buffer_{i,t} = bank\_ratio_{i,t} - supervisor\_requirements_{i,t}$$

where *supervisor\_requirements* stands for the individual Pillar II total discretionary capital requirement required by the supervisor and *bank\_ratio*$_{i,t}$ the ratio effectively reached by the bank on a consolidated basis,<fnref n="11" /> below or above the total supervisory requirement. By doing so, we implicitly assume that the larger the difference between economic and required capital, the looser the supervisory constraint. This assumption could be violated if banks anticipate Basel III so that the true constraint is not what is required at date *t* by the supervisor and/or the market but what she will require at date *t* + *i*. We are confident our sample does not suffer from this bias. Indeed, we can date the official supervisory emphasis on Basel III rules from September 2011 when the EBA (European Banking Authority) announced the objective of 9% of CET1 capital in June 2012. This affects only the last observation of our sample. Moreover, the first proposal for Basel III happened to be published only in 2010Q3. Even if we suppose French banks started to anticipate the future implementation of the new package at the end of 2010, this would only affect a negligible part of our sample.

By analyzing bank supervisor's reports on the Pillar II surcharge, it seems the French Prudential and Resolution Authority tends to favor a minimum 50-bp buffer, meaning a lower level is almost equivalent to no buffer at all for supervisors. Using this judgmental criterion, we thus single out this 50-bp threshold for *Buffer*$_{i,t}$ above which banks might be less constrained by the supervisor. Combining this qualitative and quantitative threshold with *Max*(*Buffer*$_{i,t}$), we split the distribution of *Buffer*$_{i,t}$ along three segments, two of which, above 50 bps, are of identical

<footnote n="8">⁸See http://www.eba.europa.eu/Supervisory-Reporting/COREP/COREP-framework.aspx for details.</footnote>

<footnote n="9">⁹Thus, we consider a prudential leverage ratio and not a risk-weighted solvency ratio. Since we run regressions from 2003 to 2011, the definition of RWA is not constant throughout the period. We could reproduce a *posteriori* what would have been RWA before Basel II by computing the Basel formula on bank's portfolio data. We do not consider this approach due to two caveats. First, and most importantly, this requires assuming bankers' behavior is immune to the risk weighting of solvency ratios, since they would not have adapted to the regulatory context. We proxy the risk profile of the balance-sheet by the ratio of non-performing loans to total loans granted (NPL). Second, data are not granular enough to build consistent estimates.</footnote>

<footnote n="10">¹⁰This standard technique in the banking literature may be weakened for highly autocorrelated variables. But it is not the case here. Moreover, we divide the amount of eligible Tier 1 capital by total assets whereas we only try to explain the growth of a particular item of the balance sheet, namely credit to NFCs (representing on average 10% of total assets). As the bank portfolio is re-optimized at each period, this makes the endogeneity issue less stringent.</footnote>

<footnote n="11">¹¹We therefore assume that the consolidated-level constraint affects each institution of the banking group uniformly.</footnote>
lengths. Doing so, we can define three dummy variables for each observation being in a given segment, which will constitute the basis for three different groups of banks. Precisely, we build, with $s_i$ the point defining the cut-off point between the $i^{th}$ and $i + 1^{th}$ segment,<fnref n="12" /> the three following groups of banks:

$$
\begin{align*}
\text{Group\_A}_{i,t} &= \begin{cases} 1 & \text{if } \text{Buffer}_{i,t} \le s_1 = 50\,\text{bps} \\ 0 & \text{otherwise} \end{cases} \\
\text{Group\_B}_{i,t} &= \begin{cases} 1 & \text{if } s_1 < \text{Buffer}_{i,t} \le s_2 = \frac{s_1+\text{Max}}{2} \\ 0 & \text{otherwise} \end{cases} \\
\text{Group\_C}_{i,t} &= \begin{cases} 1 & \text{if } s_2 < \text{Buffer}_{i,t} \\ 0 & \text{otherwise} \end{cases}
\end{align*}
$$

We also build the interactions between these dummies and CAT1. Doing so, we can augment
our baseline specification and estimate $(\beta_j)_{j=1,2,3}$ in :

$$
\begin{align*}
\Delta y_{it} ={}& \alpha + \beta_0(L)\text{CAT1}_{i,t} \\
& +\beta_1(L)[\text{CAT1}_{i,t} \cdot \text{Group\_A}_{i,t}] + \beta_2(L)[\text{CAT1}_{i,t} \cdot \text{Group\_B}_{i,t}] + \beta_3(L)[\text{CAT1}_{i,t} \cdot \text{Group\_C}_{i,t}] \\
& +\beta_4(L)\text{Group\_A}_{i,t} + \beta_5(L)\text{Group\_B}_{i,t} + \beta_6(L)\text{Group\_C}_{i,t} \\
& +\gamma(L)X_{i,t} + \mu_i + \lambda_t + q_t + \varepsilon_{i,t}^2
\end{align*}
$$

The different groups defined above reflect the scale of supervisory constraint faced by banks in
the sample. For instance, banks belonging to group A could be qualified as "weakly/undercapitalized"
as they barely or do not meet supervisory requirements. Being in this group means these banks
will be subject to frequent on-site inspections and prompt corrective actions which will require
them to restrict asset growth, submit a capital restoration plan etc. Thus, group-A banks are sub-
ject a priori to an intense supervisory constraint. Banks belonging to group B may be viewed as
"adequately capitalized" and they will be less likely subject to frequent inspections and corrective
actions. Finally, banks in group C could be qualified as "well capitalized" as they far exceed the
supervisory minimum requirement and therefore enjoy a higher degree of freedom in their activi-
ties in contrast with group A. Group C of the distribution of Buffer will be our reference group
from now on. We also test analogous specifications with the interactions for NPL, the ratio of
non-performing loans to the total amount of loans granted.

5.3 Estimation Method

We estimate the equations with a fixed-effect ($\mu_i$) panel data estimation procedure. We select the lag order of our control variables with the usual BIC criterion. As the Pillar-II capital surcharges are set once a year by the supervisor in France, we posit that the implied supervisory constraint may affect the bank with a lag of a few quarters, which will be determined from the value of the information criterion.

Since the Bank Lending Survey has a sample of institutions selected on a solo basis while
prudential equity capital is a group-wide measure, we have to correct for correlation between in-
dividuals that are part of the same consolidated entity.<fnref n="13" /> We do so by basing inference on a

<footnote n="12">¹²A slightly lower or higher $s_2$ does not change our overall results.</footnote>

<footnote n="13">¹³For example, teams within a same banking group compete to get the largest capital allocation for their activities.</footnote>
group-clustered estimator of the variance-covariance matrix (Wooldridge (2003)).<fnref n="14" />

Our panel is unbalanced, because of concentration dynamics in the French banking sector.<fnref n="15" /> Bank balance-sheet datasets often contain a significant number of outlier observations reflecting mergers & acquisitions (M&A) or other structural changes in a bank structure or a statistical break. With the help of information provided by the French banking supervisor, we list 32 outlier observations, 7 of them corresponding to M&A operations and the rest to take into account a structural break for one bank in the sample.<fnref n="16" /> Moreover, we had to combine bank data originating from two different databases of the French supervisor. Thus, we take this into consideration in our analysis by creating a dummy variable for the aforementioned structural break and that equals 1 at each M&A event or at each period that makes use of a different bank database (Data quality dummy). We also control for a crisis dummy in some of our specifications, which is equal to 1 from 2008q3 onwards.

# 6 Empirical results

## 6.1 Capital Requirements and Economic Capital

Table 5 presents our baseline estimation of the reduced-form equation and some alternative specifications intended as robustness checks. Column (1) presents the simplest specification with our main variable of interest (CAT1), the BLS responses and seasonal dummies, column (2) adds the macroeconomic controls (nominal investment growth by NFCs (d_Investment) and the Eonia) while column (3) incorporates time dummies.

The coefficient of the variable of interest CAT1 is always significant at the 5% level and varies only little from one specification to another. According to our baseline result, raising the ratio of Tier 1 own funds to the size of the balance sheet by 1 ppt leads, ceteris paribus, to a rise in credit growth by 1 ppt approximately. We here capture that banks with a higher capitalization will spur a more dynamic credit supply. This result is not unsettling in itself as a good chunk of our sample covers the upward part of the French credit cycle.

In practice, a positive shock to CAT1 could be implemented through 3 different ways:

* increasing the amount of Tier 1 capital (total assets being held constant),

* decreasing the amount of total assets (Tier 1 capital being held constant),

* Tier 1 capital increasing faster (or decreasing slower) than total assets.

Results presented in Table 5 point to a specific behavior of banks. In the first and third case, the bank has at disposal a greater share of capital (i.e. more unborrowed funds) which will allow it to supply more credit. Our regression reflects that feature. In the second case, the bank begins by shedding assets, leading to a higher share of capital compared to assets in the balance sheet, everything else held constant. Our results show that the bank re-accelerates its production of loans. In the light of table 5, the three cases indicate that French banks actively manage their balance sheets and their leverage. This feature echoes the work of Adrian and Shin (2010) on US

<footnote n="14">¹⁴In the end, the estimation finds 8 clusters in our sample.</footnote>

<footnote n="15">¹⁵We are subject to the survivor bias to the extent that the selection process is not independent from the error term, given all regressors. See Baltagi and Song (2006).</footnote>

<footnote n="16">¹⁶The surveyed bank switched to another branch of the consolidated group.</footnote>
<table><thead><tr><th>QoQ_NFCloans<sub>t</sub></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>CAT1<sub>t-1</sub></td><td>0.912<sup>**</sup><br>(0.363)</td><td>0.901<sup>**</sup><br>(0.318)</td><td>1.116<sup>**</sup><br>(0.411)</td></tr><tr><td>BLS_S_NoChge<sub>t-1</sub></td><td>-0.044<sup>**</sup><br>(0.017)</td><td>-0.049<sup>**</sup><br>(0.018)</td><td>-0.045<sup>**</sup><br>(0.018)</td></tr><tr><td>BLS_S_Tight<sub>t-1</sub></td><td>-0.049<sup>**</sup><br>(0.017)</td><td>-0.070<sup>***</sup><br>(0.019)</td><td>-0.056<sup>**</sup><br>(0.019)</td></tr><tr><td>BLS_D_NoChge<sub>t-2</sub></td><td>0.021<sup>**</sup><br>(0.006)</td><td>0.012<sup>*</sup><br>(0.006)</td><td>0.005<br>(0.005)</td></tr><tr><td>BLS_D_Increa<sub>t-2</sub></td><td>0.032<sup>***</sup><br>(0.008)</td><td>0.023<sup>**</sup><br>(0.008)</td><td>0.015<br>(0.009)</td></tr><tr><td>NPL<sub>t-1</sub></td><td>-0.490<br>(0.322)</td><td>-0.301<br>(0.328)</td><td>0.294<br>(0.450)</td></tr><tr><td>d_Investment<sub>t-2</sub></td><td></td><td>0.413<br>(0.228)</td><td></td></tr><tr><td>Eonia<sub>t-2</sub></td><td></td><td>0.009<sup>***</sup><br>(0.002)</td><td></td></tr><tr><td>Constant</td><td>0.016<br>(0.026)</td><td>-0.011<br>(0.024)</td><td>-0.007<br>(0.034)</td></tr><tr><td>Fixed effects</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Crisis Dummy</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Data Quality Dummy</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Time Dummies</td><td>NO</td><td>NO</td><td>YES</td></tr><tr><td>Seasonal Dummies</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Observations</td><td>382</td><td>382</td><td>382</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.066</td><td>0.094</td><td>0.115</td></tr></tbody></table>

Standard errors in parentheses

* p < 0.10, ** p < 0.05, *** p < 0.01

<caption>Table 5: Reduced form credit equation - Baseline specifications. {$BLS\_S_{i,t} = BLS\_S\_Eased_{i,t} = -1$}, {$BLS\_D_{i,t} = BLS\_D\_Decrease_{i,t} = -1$} are taken as the reference groups for the BLS variables.</caption>
commercial banks, which are found to have dynamically managed their assets and liabilities in order to maintain a constant leverage ratio.

Regarding control variables, columns (1) and (2) of table 5 show the relative relevance of the demand-related BLS variable which coefficients are positive. Aggregate loan demand by NFCs proxied here by the quarterly growth of NFCs nominal investment (d_Investment)<fnref n="17" /> turns out to be close to significativity and manages to capture some variability in our data as the coefficients of BLS-D become less significant. The time dummies in column (3) seem to wholly capture aggregate credit demand in the end. This probably reflects the lack of variance of loan demand at the individual level in our sample.

Turning to the supply side, the BLS responses related to credit standards are found to be significant at the 5% threshold with negative coefficients, i.e. tightened credit standards are associated with slower lending growth. Our results show again their high explanatory power and their relevance as in Del Giovane et al. (2011).<fnref n="18" /> However, our proxy for the monetary stance in the Euro area (column (2)) turns out to have a significant positive effect on NFCs credit growth,<fnref n="19" /> which seems at first sight surprising given that the higher financing cost for banks should translate into higher prices for NFCs and therefore a fall in demand. As in Francis and Osborne (2012) who found the same feature in the UK, our result can still be interpreted in two ways. First, policymakers may take into account bank credit when they are setting the monetary stance, and hence strong credit growth may trigger increases in the policy rate, which then take time to act on demand for credit. As a second explanation, we can envisage that, while increases in interest rates may reduce demand for credit, this change may actually result in firms becoming more dependent on banks, if an increase in the policy rate makes the access to disintermediated financing more difficult for firms (e.g. the reduction of informational asymmetries between borrowers and lenders by banks becomes more relevant during periods of tight monetary conditions, in contrast with market financing).

We fail to uncover any significant effects of the ratio of non-performing loans to total loans on credit growth with the basic specifications.

Table 6 allows the effect of the CAT1 ratio to vary with the bank group the observation belongs to. The interaction variables have been introduced with one lag in order to reflect the lagged effect of supervisory action on the bank's risk management. We find again the same significant positive effect of CAT1 on credit growth at the 5% level. But it is now higher, as it reflects the impact of CAT1 in our reference group, that is, group C (the third segment of Buffer). Results on the interactions of the CAT1 ratio with the group dummies show that the more stringent the supervisory constraint, the lower the effect of higher capital on credit growth. These results can be explained by the fact that the supervisory body limits the response of banks to an improvement of its capital ratio.

<footnote n="17">¹⁷Adding or replacing it by the change in inventories at NFCs do not change anything to our results.</footnote>

<footnote n="18">¹⁸Costs of funds and the capital position are potential factors behind the answers given to the lending standards evolution by bankers to the BLS. They are indeed explanatory items suggested by the questionnaire itself. So entering both the capital ratio and the lending standards variable from the BLS could entail double counting of the information related to capital. To make sure our estimation does not suffer from this bias, we constructed a synthetic indicator of lending standards factors answers to the BLS, excluding costs of funds and balance-sheet constraints. It left the results unchanged for CAT1.</footnote>

<footnote n="19">¹⁹Using another interest rate such as the Euribor 3M does not change our results.</footnote>
<table><thead><tr><th>QoQ_NFCloans<sub>t</sub></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>CAT1<sub>t-1</sub></td><td>1.510<sup>***</sup><br>(0.357)</td><td>1.293<sup>***</sup><br>(0.350)</td><td>1.632<sup>**</sup><br>(0.496)</td></tr><tr><td>Group_A<sub>t-2</sub></td><td>0.016<br>(0.018)</td><td>-0.015<br>(0.013)</td><td>-0.018<br>(0.019)</td></tr><tr><td>Group_B<sub>t-2</sub></td><td>0.029<sup>*</sup><br>(0.014)</td><td>0.014<br>(0.013)</td><td>0.013<br>(0.010)</td></tr><tr><td>CAT1<sub>t-1</sub> * Group_A<sub>t-2</sub></td><td>-0.459<br>(0.303)</td><td>-0.081<br>(0.214)</td><td>-0.103<br>(0.278)</td></tr><tr><td>CAT1<sub>t-1</sub> * Group_B<sub>t-2</sub></td><td>-0.772<sup>***</sup><br>(0.169)</td><td>-0.579<sup>***</sup><br>(0.116)</td><td>-0.693<sup>***</sup><br>(0.175)</td></tr><tr><td>BLS_S_NoChge<sub>t-1</sub></td><td>-0.044<sup>**</sup><br>(0.017)</td><td>-0.051<sup>**</sup><br>(0.017)</td><td>-0.047<sup>**</sup><br>(0.017)</td></tr><tr><td>BLS_S_Tight<sub>t-1</sub></td><td>-0.049<sup>**</sup><br>(0.016)</td><td>-0.071<sup>***</sup><br>(0.017)</td><td>-0.056<sup>***</sup><br>(0.016)</td></tr><tr><td>BLS_D_NoChge<sub>t-2</sub></td><td>0.021<sup>**</sup><br>(0.007)</td><td>0.013<sup>*</sup><br>(0.006)</td><td>0.004<br>(0.005)</td></tr><tr><td>BLS_D_Increa<sub>t-2</sub></td><td>0.033<sup>***</sup><br>(0.008)</td><td>0.025<sup>**</sup><br>(0.007)</td><td>0.017<sup>*</sup><br>(0.008)</td></tr><tr><td>NPL<sub>t-1</sub></td><td>-0.618<br>(0.337)</td><td>-0.461<br>(0.344)</td><td>0.192<br>(0.451)</td></tr><tr><td>d_Investment<sub>t-2</sub></td><td></td><td>0.405<br>(0.238)</td><td></td></tr><tr><td>Eonia<sub>t-2</sub></td><td></td><td>0.010<sup>***</sup><br>(0.003)</td><td></td></tr><tr><td>Constant</td><td>-0.008<br>(0.033)</td><td>-0.020<br>(0.031)</td><td>-0.020<br>(0.041)</td></tr><tr><td>Fixed effects</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Crisis Dummy</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Data Quality Dummy</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Time Dummies</td><td>NO</td><td>NO</td><td>YES</td></tr><tr><td>Seasonal Dummies</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Observations</td><td>382</td><td>382</td><td>382</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.063</td><td>0.093</td><td>0.119</td></tr></tbody></table>

Standard errors in parentheses

* p < 0.10, ** p < 0.05, *** p < 0.01

<caption>Table 6: Non-linearity induced by the supervisory constraint. {BLS_S<sub>i,t</sub> = BLS_S_Eased<sub>i,t</sub> = -1}, {BLS_D<sub>i,t</sub> = BLS_D_Decrea<sub>i,t</sub> = -1} are taken as the reference groups for the BLS variables and group C for the dummy-based variables.</caption>
We fail to find any significantly different effect for group A from group C, i.e. banks being closest to their supervisory minimum and so supposedly under intense supervisory pressure does not have an influence on the association between the capital ratio and NFCs credit growth. Moreover, we can deduce from Table 6 that the coefficients of $CAT1 * Group\_A$ and $CAT1 * Group\_B$ are not significantly different. All in all, when looking at group C on the one hand and banks of group A and B combined on the other, our empirical results show that as a bank is more and more constrained by the supervisor, its response to an improvement in the capital ratio in terms of credit growth will be lower. We would like to stress that our present results reflect banks’ behavior throughout the credit cycle.<fnref n="20" />

We refrain from commenting the results on the segment dummies themselves, since they only alter the coefficient of the constant. Results for the control variables are similar to those obtained in table 5.

Specifications that take into account the serial correlation of the dependent variable are presented in the appendix (table B.1) and confirms the previous qualitative results.

## 6.2 Capital Requirements and Non-Performing Loans

In this section, we test whether capital requirements induce non-linearity through another important risk-related variable than capital itself. We focus here on the ratio of non-performing loans to total loans granted, $NPL$ as showed in table 7. Both the capital ratio $CAT1$ and $NPL$ are standard riskmetrics and deeply linked together as rising non-performing loans may lead to the depletion of bank capital. Moreover, non-performing loans in the asset portfolio are automatically applied a 150% risk weight, which then calls for higher capital requirements. As the previous specifications did not reveal any significant linear impact of $NPL$ despite its importance as a standard bank riskmetric, this section thus attempts to uncover any potential non-linear effects of $NPL$ on credit growth.

In line with our baseline set-up in table 5, the ratio of non-performing loans is not significantly related to credit growth in the reference group (group C). In a similar way to the capital ratio, we show a higher significant negative effect as you move down across the groups of banks. This suggests that supervisory capital requirements induce the bank to be more cautious in their credit allocation, i.e. credit growth will be more responsive to non-performing loans if their share becomes too important. The estimated coefficient for group A is not always significant (see column (3) of table 7) and seems to point to the same phenomenon near the supervisory minimum requirement as for the capital ratio $CAT1$. Table B.2 in the appendix confirms this result in the case of autoregressive specifications.

## 7 Conclusion

This paper examines the different potential effects of bank capital ratio on credit growth using a bank-level analysis. It takes advantage of the bank-level answers to the Bank Lending Survey to be able to analyze the supply-side effects of capital on lending. It further makes use of the

<footnote n="20">²⁰This can be put into perspective with Carlson et al. (2013) who focus on the crisis period (2008-2010). They find that in such extreme circumstances, the elasticity of bank lending with respect to capital ratios is actually higher when capital ratios are relatively low.</footnote>
<table><thead><tr><th>QoQ_NFCloans<sub>t</sub></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>CAT1<sub>t-1</sub></td><td>0.881**<br>(0.358)</td><td>0.901**<br>(0.298)</td><td>1.173**<br>(0.392)</td></tr><tr><td>NPL<sub>t-1</sub></td><td>0.040<br>(0.311)</td><td>0.052<br>(0.370)</td><td>0.718<br>(0.482)</td></tr><tr><td>Group_A<sub>t-1</sub></td><td>0.051**<br>(0.018)</td><td>0.028<br>(0.018)</td><td>0.019<br>(0.017)</td></tr><tr><td>Group_B<sub>t-1</sub></td><td>0.021<br>(0.021)</td><td>0.010<br>(0.018)</td><td>0.004<br>(0.018)</td></tr><tr><td>NPL<sub>t-1</sub> * Group_A<sub>t-1</sub></td><td>-1.441***<br>(0.293)</td><td>-0.783**<br>(0.261)</td><td>-0.047<br>(0.455)</td></tr><tr><td>NPL<sub>t-1</sub> * Group_B<sub>t-1</sub></td><td>-0.675**<br>(0.228)</td><td>-0.502*<br>(0.214)</td><td>-0.411*<br>(0.194)</td></tr><tr><td>BLS_S_NoChge<sub>t-1</sub></td><td>-0.043*<br>(0.019)</td><td>-0.049**<br>(0.019)</td><td>-0.044*<br>(0.021)</td></tr><tr><td>BLS_S_Tight<sub>t-1</sub></td><td>-0.054**<br>(0.020)</td><td>-0.072**<br>(0.021)</td><td>-0.057**<br>(0.022)</td></tr><tr><td>BLS_D_NoChge<sub>t-2</sub></td><td>0.019**<br>(0.007)</td><td>0.012<br>(0.007)</td><td>0.006<br>(0.006)</td></tr><tr><td>BLS_D_Increa<sub>t-2</sub></td><td>0.029***<br>(0.008)</td><td>0.023**<br>(0.008)</td><td>0.014<br>(0.009)</td></tr><tr><td>d_Investment<sub>t-2</sub></td><td></td><td>0.380<br>(0.242)</td><td></td></tr><tr><td>Eonia<sub>t-2</sub></td><td></td><td>0.009**<br>(0.002)</td><td></td></tr><tr><td>Constant</td><td>-0.004<br>(0.035)</td><td>-0.019<br>(0.032)</td><td>-0.023<br>(0.044)</td></tr><tr><td>Fixed effects</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Crisis Dummy</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Data Quality Dummy</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Time Dummies</td><td>NO</td><td>NO</td><td>YES</td></tr><tr><td>Seasonal Dummies</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Observations</td><td>382</td><td>382</td><td>382</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.070</td><td>0.091</td><td>0.115</td></tr></tbody></table>

Standard errors in parentheses

* p < 0.10, ** p < 0.05, *** p < 0.01

<caption>Table 7: Non-performing loans and capital requirements. {$BLS\_S_{i,t} = BLS\_S\_Eased_{i,t} = -1$}, {$BLS\_D_{i,t} = BLS\_D\_Decrea_{i,t} = -1$} are taken as the reference groups for the BLS variables and group C for the dummy-based variables.</caption>
confidential supervisory data on discretionary capital buffers required by the French supervisor to study the impact of capital requirements on credit growth, through both capital itself and the reaction to non-performing loans.

We show that supervisory capital requirements induce non-linearity in the reaction of credit growth to the share of capital with which a bank is funded. If on average, in our sample of French banks, we find that more capital means an acceleration of credit to non-financial corporations, this result must be viewed through the lenses of the intensity of supervisory requirements, measured as the difference between regulatory and economic capital. More supervisory capital-constrained banks' credit growth tend to be less responsive to a higher capital ratio than unconstrained banks. We thus show that supervisory capital is indeed a lever to curb lending.

Moreover, we show that this non-linearity is also present with the ratio of non-performing loans to total loans granted while no linear effect is detected. More supervisory capital constrained banks tend to be more reactive to this ratio than unconstrained banks. The former are more prone to reduce credit allocation after a rise in non-performing loans than the latter.

However, both aforementioned non-linear effects seem to weaken below or close to the supervisory minimum capital requirement.

This variation of the impact of both capital and non-performing loans with the intensity of supervisory capital constraints would have to be accounted for when designing the policy mix to fulfill macro-prudential objectives. Indeed, capital instruments are prominent in the macro-prudential policymaker toolkit. She can set countercyclical capital buffer, systemic risk buffer, G-SIFIs and D-SIFIs buffers. But she can also modify RWA weights on the housing sector or put limits on interbank exposures. Only the knowledge of the constraint being binding or not would allow her to anticipate the proper impact of the capital requirement on bank lending to the real economy. If the constraint is not binding for the most prominent players, other tools would have to be considered. If the constraint is not uniformly binding for all banks, secondary effects would probably arise, with credit supply distortions or substitutions.
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## A Sample's representativity

<figure><img src="image_6.png" /><figcaption>Figure A.1: Ratio of sample's assets on total aggregate banking assets.</figcaption></figure>

## B Reduced-form equation: robustness checks

### B.1 With *CAT1*

Table B.1 takes into account the serial correlation of the dependent variable. These autoregressive models are also estimated with a standard fixed-effect routine following Judson and Owen (1999) results on panel with the time dimension larger than the cross-sectional one.

### B.2 With *NPL*

Table B.2 takes into account the serial correlation of the dependent variable in the non-performing loans setting. Results are globally consistent with those underlined in the core of the paper.
<table><thead><tr><th></th><th>(1)</th><th>(2)</th><th>(3)</th></tr></thead><tbody><tr><td>QoQ_NFCloans<sub>t</sub></td><td></td><td></td><td></td></tr><tr><td>QoQ_NFCloans<sub>t-1</sub></td><td>-0.119**<br>(0.049)</td><td>-0.107**<br>(0.045)</td><td>-0.131**<br>(0.047)</td></tr><tr><td>CAT1<sub>t-1</sub></td><td>1.177**<br>(0.478)</td><td>1.437***<br>(0.410)</td><td>1.772**<br>(0.570)</td></tr><tr><td>NPL<sub>t-1</sub></td><td>0.193<br>(0.446)</td><td>-0.482<br>(0.329)</td><td>0.093<br>(0.458)</td></tr><tr><td>Group_A<sub>t-2</sub></td><td></td><td>-0.010<br>(0.013)</td><td>-0.014<br>(0.021)</td></tr><tr><td>Group_B<sub>t-2</sub></td><td></td><td>0.019<br>(0.013)</td><td>0.016<br>(0.010)</td></tr><tr><td>CAT1<sub>t-1</sub> * Group_A<sub>t-2</sub></td><td></td><td>-0.147<br>(0.219)</td><td>-0.162<br>(0.341)</td></tr><tr><td>CAT1<sub>t-1</sub> * Group_B<sub>t-2</sub></td><td></td><td>-0.684***<br>(0.130)</td><td>-0.777***<br>(0.187)</td></tr><tr><td>BLS_S_NoChge<sub>t-1</sub></td><td>-0.048*<br>(0.020)</td><td>-0.053**<br>(0.018)</td><td>-0.049**<br>(0.019)</td></tr><tr><td>BLS_S_Tight<sub>t-1</sub></td><td>-0.059**<br>(0.022)</td><td>-0.074***<br>(0.018)</td><td>-0.059**<br>(0.018)</td></tr><tr><td>BLS_D_NoChge<sub>t-2</sub></td><td>0.007<br>(0.006)</td><td>0.015*<br>(0.007)</td><td>0.006<br>(0.007)</td></tr><tr><td>BLS_D_Increa<sub>t-2</sub></td><td>0.019*<br>(0.009)</td><td>0.030**<br>(0.010)</td><td>0.022**<br>(0.009)</td></tr><tr><td>d_Investment<sub>t-2</sub></td><td></td><td>0.403<br>(0.245)</td><td></td></tr><tr><td>Eonia<sub>t-2</sub></td><td></td><td>0.012***<br>(0.002)</td><td></td></tr><tr><td>Constant</td><td>-0.013<br>(0.038)</td><td>-0.037<br>(0.037)</td><td>-0.030<br>(0.045)</td></tr><tr><td>Fixed effects</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Crisis Dummy</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Data Quality Dummy</td><td>YES</td><td>YES</td><td>YES</td></tr><tr><td>Time Dummies</td><td>YES</td><td>NO</td><td>YES</td></tr><tr><td>Seasonal Dummies</td><td>YES</td><td>YES</td><td>NO</td></tr><tr><td>Observations</td><td>381</td><td>381</td><td>381</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.123</td><td>0.106</td><td>0.130</td></tr></tbody></table>

Standard errors in parentheses

* p < 0.10, ** p < 0.05, *** p < 0.01

<caption>Table B.1: Robustness checks : AR specifications. {$BLS\_S_{i,t} = BLS\_S\_Eased_{i,t} = -1$}, {$BLS\_D_{i,t} = BLS\_D\_Decrea_{i,t} = -1$} are taken as the reference groups for the BLS variables and group C for the dummy-based variables.</caption>
<table><thead><tr><th></th><th>(1)</th><th>(2)</th></tr></thead><tbody><tr><td>QoQ_NFCloans<sub>t</sub></td><td></td><td></td></tr><tr><td>QoQ_NFCloans<sub>t-1</sub></td><td>-0.110**<br>(0.042)</td><td>-0.130**<br>(0.045)</td></tr><tr><td>CAT1<sub>t-1</sub></td><td>0.966**<br>(0.356)</td><td>1.241**<br>(0.464)</td></tr><tr><td>NPL<sub>t-1</sub></td><td>0.066<br>(0.379)</td><td>0.637<br>(0.498)</td></tr><tr><td>Group_A<sub>t-1</sub></td><td>0.033<br>(0.020)</td><td>0.023<br>(0.020)</td></tr><tr><td>Group_B<sub>t-1</sub></td><td>0.012<br>(0.020)</td><td>0.004<br>(0.021)</td></tr><tr><td>NPL<sub>t-1</sub> * Group_A<sub>t-1</sub></td><td>-0.883**<br>(0.286)</td><td>-0.154<br>(0.468)</td></tr><tr><td>NPL<sub>t-1</sub> * Group_B<sub>t-1</sub></td><td>-0.533*<br>(0.255)</td><td>-0.434*<br>(0.217)</td></tr><tr><td>BLS_S_NoChge<sub>t-1</sub></td><td>-0.051**<br>(0.021)</td><td>-0.046*<br>(0.023)</td></tr><tr><td>BLS_S_Tight<sub>t-1</sub></td><td>-0.076**<br>(0.023)</td><td>-0.060**<br>(0.025)</td></tr><tr><td>BLS_D_NoChge<sub>t-2</sub></td><td>0.014<br>(0.008)</td><td>0.007<br>(0.007)</td></tr><tr><td>BLS_D_Increa<sub>t-2</sub></td><td>0.027**<br>(0.010)</td><td>0.019*<br>(0.010)</td></tr><tr><td>d_Investment<sub>t-2</sub></td><td>0.374<br>(0.248)</td><td></td></tr><tr><td>Eonia<sub>t-2</sub></td><td>0.010***<br>(0.002)</td><td></td></tr><tr><td>Constant</td><td>-0.034<br>(0.038)</td><td>-0.031<br>(0.048)</td></tr><tr><td>Fixed effects</td><td>YES</td><td>YES</td></tr><tr><td>Crisis Dummy</td><td>YES</td><td>NO</td></tr><tr><td>Data Quality Dummy</td><td>YES</td><td>YES</td></tr><tr><td>Time Dummies</td><td>NO</td><td>YES</td></tr><tr><td>Seasonal Dummies</td><td>YES</td><td>NO</td></tr><tr><td>Observations</td><td>381</td><td>381</td></tr><tr><td>Adjusted R<sup>2</sup></td><td>0.104</td><td>0.125</td></tr></tbody></table>

Standard errors in parentheses

* p < 0.10, ** p < 0.05, *** p < 0.01

<caption>Table B.2: Non-performing loans and serial correlation for credit growth. {BLS_S<sub>i,t</sub> = BLS_S_Eased<sub>i,t</sub> = -1}, {BLS_D<sub>i,t</sub> = BLS_D_Decrea<sub>i,t</sub> = -1} are taken as the reference groups for the BLS variables and group C for the dummy-based variables.</caption>
<table><tr><td>G 9001</td><td>J. FAYOLLE et M. FLEURBAEY<br>Accumulation, profitabilité et endettement des entreprises</td><td>Macro-economic import functions with imperfect competition - An application to the E.C. Trade</td></tr><tr><td>G 9002</td><td>H. ROUSSE<br>Détection et effets de la multicolinéarité dans les modèles linéaires ordinaires - Un prolongement de la réflexion de BELSLEY, KUH et WELSCH</td><td>G 9203<br>I. STAPIC<br>Les échanges internationaux de services de la France dans le cadre des négociations multilatérales du GATT<br>Jun 1992 (1ère version)<br>Novembre 1992 (version finale)</td></tr><tr><td>G 9003</td><td>P. RALLE et J. TOUJAS-BERNATE<br>Indexation des salaires : la rupture de 1983</td><td>G 9204<br>P. SEVESTRE<br>L'économie sur données individuelles-temporelles. Une note introductive</td></tr><tr><td>G 9004</td><td>D. GUELLEC et P. RALLE<br>Compétitivité, croissance et innovation de produit</td><td>G 9205<br>H. ERKEL-ROUSSE<br>Le commerce extérieur et l'environnement international dans le modèle AMADEUS (réestimation 1992)</td></tr><tr><td>G 9005</td><td>P. RALLE et J. TOUJAS-BERNATE<br>Les conséquences de la désindexation. Analyse dans une maquette prix-salaires</td><td>G 9206<br>N. GREENAN et D. GUELLEC<br>Coordination within the firm and endogenous growth</td></tr><tr><td>G 9101</td><td>Équipe AMADEUS<br>Le modèle AMADEUS - Première partie - Présentation générale</td><td>G 9207<br>A. MAGNIER et J. TOUJAS-BERNATE<br>Technology and trade: empirical evidences for the major five industrialized countries</td></tr><tr><td>G 9102</td><td>J.L. BRILLET<br>Le modèle AMADEUS - Deuxième partie - Propriétés variantielles</td><td>G 9208<br>B. CREPON, E. DUGUET, D. ENCAOUA et P. MOHNEN<br>Cooperative, non cooperative R & D and optimal patent life</td></tr><tr><td>G 9103</td><td>D. GUELLEC et P. RALLE<br>Endogenous growth and product innovation</td><td>G 9209<br>B. CREPON et E. DUGUET<br>Research and development, competition and innovation: an application of pseudo maximum likelihood methods to Poisson models with heterogeneity</td></tr><tr><td>G 9104</td><td>H. ROUSSE<br>Le modèle AMADEUS - Troisième partie - Le commerce extérieur et l'environnement international</td><td>G 9301<br>J. TOUJAS-BERNATE<br>Commerce international et concurrence impartie: développements récents et implications pour la politique commerciale</td></tr><tr><td>G 9105</td><td>H. ROUSSE<br>Effets de demande et d'offre dans les résultats du commerce extérieur manufacturé de la France au cours des deux dernières décennies</td><td>G 9302<br>Ch. CASES<br>Durées de chômage et comportements d'offre de travail : une revue de la littérature</td></tr><tr><td>G 9106</td><td>B. CREPON<br>Innovation, taille et concentration : causalités et dynamiques</td><td>G 9303<br>H. ERKEL-ROUSSE<br>Union économique et monétaire : le débat économique</td></tr><tr><td>G 9107</td><td>B. AMABLE et D. GUELLEC<br>Un panorama des théories de la croissance endogène</td><td>G 9304<br>N. GREENAN - D. GUELLEC / G. BROUSSAUDIER - L. MIOTTI<br>Innovation organisationnelle, dynamisme technologique et performances des entreprises</td></tr><tr><td>G 9108</td><td>M. GLAUDE et M. MOUTARDIER<br>Une évaluation du coût direct de l'enfant de 1979 à 1989</td><td>G 9305<br>P. JAILLARD<br>Le traité de Maastricht : présentation juridique et historique</td></tr><tr><td>G 9109</td><td>P. RALLE et alii<br>France - Allemagne : performances économiques comparées</td><td>G 9306<br>J.L. BRILLET<br>Micro-DMS : présentation et propriétés</td></tr><tr><td>G 9110</td><td>J.L. BRILLET<br>Micro-DMS<br>NON PARU</td><td>G 9307<br>J.L. BRILLET<br>Micro-DMS - variantes : les tableaux</td></tr><tr><td>G 9111</td><td>A. MAGNIER<br>Effets accélérateur et multiplicateur en France depuis 1970 : quelques résultats empiriques</td><td>G 9308<br>S. JACOBZONE<br>Les grands réseaux publics français dans une perspective européenne</td></tr><tr><td>G 9112</td><td>B. CREPON et G. DUREAU<br>Investissement en recherche-développement : analyse de causalités dans un modèle d'accélérateur généralisé</td><td>G 9309<br>L. BLOCH - B. CŒURÉ<br>Profitabilité de l'investissement productif et transmission des chocs financiers</td></tr><tr><td>G 9113</td><td>J.L. BRILLET, H. ERKEL-ROUSSE, J. TOUJAS-BERNATE<br>"France-Allemagne Couplées" - Deux économies vues par une maquette macro-économétrique</td><td>G 9400<br>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les théories sur la structure optimale du capital : quelques points de repère</td></tr><tr><td>G 9201</td><td>W.J. ADAMS, B. CREPON, D. ENCAOUA<br>Choix technologiques et stratégies de dissuasion d'entrée</td><td>G 9410<br>F. ROSENWALD<br>Suivi conjoncturel de l'investissement</td></tr><tr><td>G 9202</td><td>J. OLIVEIRA-MARTINS, J. TOUJAS-BERNATE</td><td>G 9411<br>J. BOURDIEU - B. COLIN-SEDILLOT<br>Les décisions de financement des entreprises</td></tr></table>

<table><tr><td>G 9312</td><td>L. BLOCH - B. CŒURÉ<br>Q de Tobin marginal et transmission des chocs financiers</td></tr><tr><td>G 9313</td><td>Équipes Amadeus (INSEE), Banque de France, Métric (DP)<br>Presentation des propriétés des principaux modèles macroéconomiques du Service Public</td></tr><tr><td>G 9314</td><td>B. CREPON - E. DUGUET<br>Research & Development, competition and innovation</td></tr><tr><td>G 9315</td><td>B. DORMONT<br>Quelle est l'influence du coût du travail sur l'emploi ?</td></tr><tr><td>G 9316</td><td>D. BLANCHET - C. BROUSSE<br>Deux études sur l'âge de la retraite</td></tr><tr><td>G 9317</td><td>D. BLANCHET<br>Répartition du travail dans une population hétérogène : deux notes</td></tr><tr><td>G 9318</td><td>D. EYSSARTIER - N. PONTY<br>AMADEUS - an annual macro-economic model for the medium and long term</td></tr><tr><td>G 9319</td><td>G. CETTE - Ph. CUNÉO - D. EYSSARTIER - J. GAUTIÉ<br>Les effets sur l'emploi d'un abaissement du coût du travail des jeunes</td></tr><tr><td>G 9401</td><td>D. BLANCHET<br>Les structures par âge importent-elles ?</td></tr><tr><td>G 9402</td><td>J. GAUTIÉ<br>Le chômage des jeunes en France : problème de formation ou phénomène de file d'attente ?<br>Quelques éléments du débat</td></tr><tr><td>G 9403</td><td>P. QUIRION<br>Les déchets en France : éléments statistiques et économiques</td></tr><tr><td>G 9404</td><td>D. LADIRAY - M. GRUN-REHOMME<br>Lissage par moyennes mobiles - Le problème des extrémités de série</td></tr><tr><td>G 9405</td><td>V. MAILLARD<br>Theorie et pratique de la correction des effets de jours ouvrables</td></tr><tr><td>G 9406</td><td>F. ROSENWALD<br>La décision d'investir</td></tr><tr><td>G 9407</td><td>S. JACOBZONE<br>Les apports de l'économie industrielle pour définir la stratégie économique de l'hôpital public</td></tr><tr><td>G 9408</td><td>L. BLOCH, J. BOURDIEU, B. COLIN-SEDILLOT, G. LONGUEVILLE<br>Du défaut de paiement au dépôt de bilan : les banquiers face aux PME en difficulté</td></tr><tr><td>G 9409</td><td>D. EYSSARTIER, P. MAIRE<br>Impacts macro-économiques de mesures d'aide au logement - quelques éléments d'évaluation</td></tr><tr><td>G 9410</td><td>F. ROSENWALD<br>Suivi conjoncturel de l'investissement</td></tr><tr><td>G 9411</td><td>C. DEFEUILLE - Ph. QUIRION<br>Les déchets d'emballages ménagers : une analyse économique des politiques française et allemande</td></tr></table>

<table><tr><td>G 9412</td><td>J. BOURDIEU - B. CŒURÉ - B. COLIN-SEDILLOT<br>Investissement, incertitude et irréversibilité<br>Quelques développements récents de la théorie de l'investissement</td></tr><tr><td>G 9413</td><td>B. DORMONT - M. PAUCHET<br>L'évaluation de l'élasticité emploi-salaire dépend-elle des structures de qualification ?</td></tr><tr><td>G 9414</td><td>I. KABLA<br>Le Choix de breveter une invention</td></tr><tr><td>G 9501</td><td>J. BOURDIEU - B. CŒURÉ - B. SEDILLOT<br>Irreversible Investment and Uncertainty: When is there a Value of Waiting?</td></tr><tr><td>G 9502</td><td>L. BLOCH - B. CŒURÉ<br>Imperfections du marché du crédit, investissement des entreprises et cycle économique</td></tr><tr><td>G 9503</td><td>D. GOUX - E. MAURIN<br>Les transformations de la demande de travail par qualification en France<br>Une étude sur la période 1970-1993</td></tr><tr><td>G 9504</td><td>N. GREENAN<br>Technologie, changement organisationnel, qualifications et emploi : une étude empirique sur l'industrie manufacturière</td></tr><tr><td>G 9505</td><td>D. GOUX - E. MAURIN<br>Persistance des hiérarchies sectorielles de salaires: un réexamen sur données françaises</td></tr><tr><td>G 9505<br>Bis</td><td>D. GOUX - E. MAURIN<br>Persistance of inter-industry wages differentials: a reexamination on matched worker-firm panel data</td></tr><tr><td>G 9506</td><td>S. JACOBZONE<br>Les liens entre RMI et chômage, une mise en perspective<br>NON PARU - article sorti dans Économie et Prévision n° 122 (1996) - pages 95 à 113</td></tr><tr><td>G 9507</td><td>G. CETTE - S. MAHFOUZ<br>Le partage primaire du revenu<br>Constat descriptif sur longue période</td></tr><tr><td>G 9601</td><td>Banque de France - CEPREMAP - Direction de la Prévision - Érasme - INSEE - OFCE<br>Structures et propriétés de cinq modèles macro-économiques français</td></tr><tr><td>G 9602</td><td>Rapport d'activité de la DESE de l'année 1995</td></tr><tr><td>G 9603</td><td>J. BOURDIEU - A. DRAZNIEKS<br>L'octroi de crédit aux PME : une analyse à partir d'informations bancaires</td></tr><tr><td>G 9604</td><td>A. TOPIOL-BENSAÎD<br>Les implantations japonaises en France</td></tr><tr><td>G 9605</td><td>P. GENIER - S. JACOBZONE<br>Comportements de prévention, consommation d'alcool et tabagie : peut-on parler d'une gestion globale du capital santé ?<br>Une modélisation microéconométrique empirique</td></tr><tr><td>G 9606</td><td>C. DOZ - F. LENGLART<br>Factor analysis and unobserved component models: an application to the study of French business surveys</td></tr><tr><td>G 9607</td><td>N. GREENAN - D. GUELLEC<br>La théorie coopérative de la firme</td></tr></table>
<table><tr><td>G 9608</td><td>N. GREENAN - D. GUELLEC<br>Technological innovation and employment<br>reallocation</td></tr><tr><td>G 9609</td><td>Ph. COUR - F. RUPPRECHT<br>L'intégration asymétrique au sein du continent<br>américain : un essai de modélisation</td></tr><tr><td>G 9610</td><td>S. DUCHENE - G. FORGEOT - A. JACQUOT<br>Analyse des évolutions récentes de la productivité apparente du travail</td></tr><tr><td>G 9611</td><td>X. BONNET - S. MAHFOUZ<br>The influence of different specifications of<br>wages-prices spirals on the measure of the<br>NAIRU: the case of France</td></tr><tr><td>G 9612</td><td>PH. COUR - E. DUBOIS, S. MAHFOUZ,<br>J. PISANI-FERRY<br>The cost of fiscal retrenchment revisited: how<br>strong is the evidence?</td></tr><tr><td>G 9613</td><td>A. JACQUOT<br>Les flexions des taux d'activité sont-elles seule-<br>ment conjoncturelles ?</td></tr><tr><td>G 9614</td><td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique Français-Chinois</td></tr><tr><td>G 9701</td><td>J.L. SCHNEIDER<br>La taxe professionnelle : éléments de cadrage<br>économique</td></tr><tr><td>G 9702</td><td>J.L. SCHNEIDER<br>Transition et stabilité politique d'un système<br>redistributif</td></tr><tr><td>G 9703</td><td>D. GOUX - E. MAURIN<br>Train or Pay: Does it Reduce Inequalities to En-<br>courage Firms to Train their Workers?</td></tr><tr><td>G 9704</td><td>P. GENIER<br>Deux contributions sur dépendance et équité</td></tr><tr><td>G 9705</td><td>E. DUGUET - N. IUNG<br>R & D Investment, Patent Life and Patent Value<br>An Econometric Analysis at the Firm Level</td></tr><tr><td>G 9706</td><td>M. HOUBEBINE - A. TOPIOL-BENSAÏD<br>Les entreprises internationales en France : une<br>analyse à partir de données individuelles</td></tr><tr><td>G 9707</td><td>M. HOUBEBINE<br>Polarisation des activités et spécialisation des<br>départements en France</td></tr><tr><td>G 9708</td><td>E. DUGUET - N. GREENAN<br>Le biais technologique : une analyse sur don-<br>nées individuelles</td></tr><tr><td>G 9709</td><td>J.L. BRILLET<br>Analyzing a small French ECM Model</td></tr><tr><td>G 9710</td><td>J.L. BRILLET<br>Formalizing the transition process: scenarios for<br>capital accumulation</td></tr><tr><td>G 9711</td><td>G. FORGEOT - J. GAUTIÉ<br>Insertion professionnelle des jeunes et proces-<br>sus de déclassement</td></tr><tr><td>G 9712</td><td>E. DUBOIS<br>High Real Interest Rates: the Consequence of a<br>Saving Investment Disequilibrium or of an in-<br>sufficient Credibility of Monetary Authorities?</td></tr><tr><td>G 9713</td><td>Bilan des activités de la Direction des Études<br>et Synthèses Économiques - 1996</td></tr></table>

<table><tr><td>G 9714</td><td>F. LEQUILLER<br>Does the French Consumer Price Index Over-<br>state Inflation?</td></tr><tr><td>G 9715</td><td>X. BONNET<br>Peut-on mettre en évidence les rigidités à la<br>baisse des salaires nominaux ?<br>Une étude sur quelques grands pays de l'OCDE</td></tr><tr><td>G 9716</td><td>N. IUNG - F. RUPPRECHT<br>Productivité de la recherche et rendements<br>d'échelle dans le secteur pharmaceutique<br>français</td></tr><tr><td>G 9717</td><td>E. DUGUET - I. KABLA<br>Appropriation strategy and the motivations to use<br>the patent system in France - An econometric<br>analysis at the firm level</td></tr><tr><td>G 9718</td><td>L.P. PELÉ - P. RALLE<br>Âge de la retraite : les aspects incitatifs du ré-<br>gime général</td></tr><tr><td>G 9719</td><td>ZHANG Yingxiang - SONG Xueqing<br>Lexique macroéconomique français-chinois,<br>chinois-français</td></tr><tr><td>G 9720</td><td>M. HOUBEBINE - J.L. SCHNEIDER<br>Mesurer l'influence de la fiscalité sur la locali-<br>sation des entreprises</td></tr><tr><td>G 9721</td><td>A. MOUROUGANE<br>Crédibilité, indépendance et politique monétaire<br>Une revue de la littérature</td></tr><tr><td>G 9722</td><td>P. AUGERAUD - L. BRIOT<br>Les données comptables d'entreprises<br>Le système intermédiaire d'entreprises<br>Passage des données individuelles aux données<br>sectorielles</td></tr><tr><td>G 9723</td><td>P. AUGERAUD - J.E. CHAPRON<br>Using Business Accounts for Compiling National<br>Accounts: the French Experience</td></tr><tr><td>G 9724</td><td>P. AUGERAUD<br>Les comptes d'entreprise par activités - Le pas-<br>sage aux comptes - De la comptabilité<br>d'entreprise à la comptabilité nationale - A<br>parfait</td></tr><tr><td>G 9801</td><td>H. MICHAUDON - C. PRIGENT<br>Présentation du modèle AMADEUS</td></tr><tr><td>G 9802</td><td>J. ACCARDO<br>Une étude de comptabilité générationnelle<br>pour la France en 1996</td></tr><tr><td>G 9803</td><td>X. BONNET - S. DUCHÈNE<br>Apports et limites de la modélisation<br>« Real Business Cycles »</td></tr><tr><td>G 9804</td><td>C. BARLET - C. DUGUET -<br>D. ENCAOUA - J. PRADEL<br>The Commercial Success of Innovations<br>An econometric analysis at the firm level in<br>French manufacturing</td></tr><tr><td>G 9805</td><td>P. CAHUC - Ch. GIANELLA -<br>D. GOUX - A. ZILBERBERG<br>Equalizing Wage Differences and Bargaining<br>Power - Evidence form a Panel of French Firms</td></tr><tr><td>G 9806</td><td>J. ACCARDO - M. JLASSI<br>La productivité globale des facteurs entre 1975<br>et 1996</td></tr><tr><td>G 9807</td><td>Bilan des activités de la Direction des Études et<br>Synthèses Économiques - 1997</td></tr></table>

<table><tr><td>G 9808</td><td>A. MOUROUGANE<br>Can a Conservative Governor Conduct an Ac-<br>comodative Monetary Policy?</td></tr><tr><td>G 9809</td><td>X. BONNET - E. DUBOIS - L. FAUVET<br>Asymétrie des inflations relatives et menus costs<br>: tests sur l'inflation française</td></tr><tr><td>G 9810</td><td>E. DUGUET - N. IUNG<br>Sales and Advertising with Spillovers at the firm<br>level: Estimation of a Dynamic Structural Model<br>on Panel Data</td></tr><tr><td>G 9811</td><td>J.P. BERTHIER<br>Congestion urbaine : un modèle de trafic de<br>pointe à courbe débit-vitesse et demande<br>élastique</td></tr><tr><td>G 9812</td><td>C. PRIGENT<br>La part des salaires dans la valeur ajoutée : une<br>approche macroéconomique</td></tr><tr><td>G 9813</td><td>A.Th. AERTS<br>L'évolution de la part des salaires dans la valeur<br>ajoutée en France reflète-t-elle les évolutions<br>individuelles sur la période 1979-1994 ?</td></tr><tr><td>G 9814</td><td>B. SALANIÉ<br>Guide pratique des séries non-stationnaires</td></tr><tr><td>G 9901</td><td>S. DUCHÈNE - A. JACQUOT<br>Une croissance plus riche en emplois depuis le<br>début de la décennie ? Une analyse en compa-<br>raison internationale</td></tr><tr><td>G 9902</td><td>Ch. COLIN<br>Modélisation des carrières dans Destinie</td></tr><tr><td>G 9903</td><td>Ch. COLIN<br>Évolution de la dispersion des salaires : un essai<br>de prospective par microsimulation</td></tr><tr><td>G 9904</td><td>B. CREPON - N. IUNG<br>Innovation, emploi et performances</td></tr><tr><td>G 9905</td><td>B. CREPON - Ch. GIANELLA<br>Wages inequalities in France 1969-1992<br>An application of quantile regression techniques</td></tr><tr><td>G 9906</td><td>C. BONNET - R. MAHIEU<br>Microsimulation techniques applied to inter-<br>generational transfers - Pensions in a dynamic<br>framework: the case of France</td></tr><tr><td>G 9907</td><td>F. ROSENWALD<br>L'impact des contraintes financières dans la dé-<br>cision d'investissement</td></tr><tr><td>G 9908</td><td>Bilan des activités de la DESE - 1998</td></tr><tr><td>G 9909</td><td>J.P. ZOYEM<br>Contrat d'insertion et sortie du RMI<br>Réalisation des effets d'une politique sociale</td></tr><tr><td>G 9910</td><td>Ch. COLIN - FI. LEGROS - R. MAHIEU<br>Bilans contributifs comparés des régimes de<br>retraite du secteur privé et de la fonction<br>publique</td></tr><tr><td>G 9911</td><td>G. LAROQUE - B. SALANIÉ<br>Une décomposition du non-emploi en France</td></tr><tr><td>G 9912</td><td>B. SALANIÉ<br>Une maquette analytique de long terme du<br> marché du travail</td></tr><tr><td>G 9912<br>Bis</td><td>Ch. GIANELLA<br>Une estimation de l'élasticité de l'emploi peu<br>qualifié à son coût</td></tr></table>

<table><tr><td>G 9913</td><td>Division « Redistribution et Politiques Sociales »<br>Le modèle de microsimulation dynamique<br>DESTINIE</td></tr><tr><td>G 9914</td><td>E. DUGUET<br>Macro-commandes SAS pour l'économétrie des<br>panels et des variables qualitatives</td></tr><tr><td>G 9915</td><td>R. DUHAUTOIS<br>Évolution des flux d'emplois en France entre<br>1990 et 1996 : une étude empirique à partir du<br>fichier des bénéfices réels normaux (BRN)</td></tr><tr><td>G 9916</td><td>J.Y. FOURNIER<br>Extraction du cycle des affaires : la méthode de<br>Baxter et King</td></tr><tr><td>G 9917</td><td>B. CRÉPON - R. DESPLATZ - J. MAIRESSE<br>Estimating price cost margins, scale economies<br>and workers' bargaining power at the firm level</td></tr><tr><td>G 9918</td><td>Ch. GIANELLA - Ph. LAGARDE<br>Productivity of hours in the aggregate production<br>function: an evaluation on a panel of French<br>firms from the manufacturing sector</td></tr><tr><td>G 9919</td><td>S. AUDRIC - P. GIVORD - C. PROST<br>Évolution de l'emploi et des coûts par quali-<br>fication entre 1982 et 1996</td></tr><tr><td>G 2000/01</td><td>R. MAHIEU<br>Les déterminants des dépenses de santé : une<br>approche macroéconomique</td></tr><tr><td>G 2000/02</td><td>C. ALLARD-PRIGENT - H. GUILMEAU -<br>A. QUINET<br>The real exchange rate as the relative price of<br>nontrables in terms of tradables: theoretical<br>investigation and empirical study on French data</td></tr><tr><td>G 2000/03</td><td>J.-Y. FOURNIER<br>L'approximation du filtre passe-bande proposée<br>par Christiano et Fitzgerald</td></tr><tr><td>G 2000/04</td><td>Bilan des activités de la DESE - 1999</td></tr><tr><td>G 2000/05</td><td>B. CREPON - F. ROSENWALD<br>Investissement et contraintes de financement : le<br>poids du cycle<br>Une estimation sur données françaises</td></tr><tr><td>G 2000/06</td><td>A. FLIPO<br>Les comportements matrimoniaux de fait</td></tr><tr><td>G 2000/07</td><td>R. MAHIEU - B. SÉDILLOT<br>Microsimulations of the retirement decision: a<br>supply side approach</td></tr><tr><td>G 2000/08</td><td>C. AUDENIS - C. PROST<br>Déficit conjoncturel : une prise en compte des<br>conjonctures passées</td></tr><tr><td>G 2000/09</td><td>R. MAHIEU - B. SÉDILLOT<br>Équivalent patrimonial de la rente et souscription<br>de retraite complémentaire</td></tr><tr><td>G 2000/10</td><td>R. DUHAUTOIS<br>Ralentissement de l'investissement : petites ou<br>grandes entreprises ? industrie ou tertiaire ?</td></tr><tr><td>G 2000/11</td><td>G. LAROQUE - B. SALANIÉ<br>Temps partiel féminin et incitations financières à<br>l'emploi</td></tr><tr><td>G 2000/12</td><td>Ch. GIANELLA<br>Local unemployment and wages</td></tr><tr><td>G 2000/13</td><td>B. CREPON - Th. HECKEL<br>- Informatisation en France : une évaluation à<br>partir de données individuelles</td></tr></table>
- Computerization in France: an evaluation based on individual company data

G2001/01 F. LEQUILLER

- La nouvelle économie et la mesure du croissance du PIB

- The new economy and the measurement of GDP growth

G2001/02 S. AUDRIC

La reprise de la croissance de l'emploi profonde aussi aux non-diplômés ?

G2001/03 I. BRAUN-LEMAIRE

Évolution et répartition du surplus de productivité

G2001/04 A. BEAUDU - Th. HECKEL

Le canal du crédit fonctionne-t-il en Europe ? Une étude de l'hétérogénéité des comportements d'investissement à partir de données de bilan agrégées

G2001/05 C. AUDENIS - P. BISCOURP -

N. FOURCADE - O. LOISEL

Testing the augmented Solow growth model: An empirical reassessment using panel data

G2001/06 R. MAHIEU - B. SÉDILLOT

Départ à la retraite, irréversibilité et incertitude

G2001/07 Bilan des activités de la DESE - 2000

G2001/08 J. Ph. GAUDEMET

Les dispositifs d'acquisition à titre facultatif d'annuités viagères de retraite

G2001/09 B. CRÉPON - Ch. GIANELLA

Fiscalité, coût d'usage du capital et demande de facteurs : une analyse sur données individuelles

G2001/10 B. CRÉPON - R. DESPLATZ

Évaluation des effets des dispositifs d'allégements de charges sociales sur les bas salaires

G2001/11 J.-Y. FOURNIER

Comparaison des salaires des secteurs public et privé

G2001/12 J.-P. BERTHIER - C. JAULENT

R. CONVENEVOLE - S. PISANI

Une méthodologie de comparaison entre consommations intermédiaires de source fiscale et de comptabilité nationale

G2001/13 P. BISCOURP - Ch. GIANELLA

Substitution and complementarity between capital, skilled and less skilled workers: an analysis at the firm level in the French manufacturing industry

G2001/14 I. ROBERT-BOBEE

Modelling demographic behaviours in the French microsimulation model Destinie: An analysis of future change in completed fertility

G2001/15 J.-P. ZOYEM

Diagnostic sur la pauvreté et calendrier de revenus : le cas du "Panel européen des ménages"

G2001/16 J.-Y. FOURNIER - P. GIVORD

La réduction des taux d'activité aux âges extrêmes, une spécificité française ?

G2001/17 C. AUDENIS - P. BISCOURP - N. RIEDINGER

Existe-t-il une asymétrie dans la transmission du prix du brut aux prix des carburants ?

G2002/01 F. MAGNIEN - J.-L. TAVERNIER - D. THESMAR

Les statistiques internationales de PIB par habitant en standard de pouvoir d'achat : une analyse des résultats

G2002/02 Bilan des activités de la DESE - 2001

G2002/03 B. SÉDILLOT - E. WALRAET

La cessation d'activité au sein des couples : y a-t-il interdépendance des choix ?

G2002/04 G. BRILHAULT

- Rétroposition des séries de FBCF et calcul du capital fixe en SEC-95 dans les comptes nationaux français

- Rétroposition of the investment series (GFCF) and estimation of fixed capital stocks on the ESA-95 basis for the French balance sheets

G2002/05 P. BISCOURP - B. CRÉPON - T. HECKEL - N.

RIEDINGER
How do firms respond to cheaper computers? Microeconomic evidence for France based on a production function approach

G2002/06 C. AUDENIS - J. DEROYON - N. FOURCADE

L'impact des nouvelles technologies de l'information et de la communication sur l'économie française - un bouclage macro-économique

G2002/07 J. BARDAJI - B. SÉDILLOT - E. WALRAET

Évaluation de trois réformes du Régime Général d'assurance vieillesse à l'aide du modèle de microsimulation DESTINIE

G2002/08 J.-P. BERTHIER

Réflexions sur les différentes notions de volume dans les comptes nationaux : comptes aux prix d'une année fixe ou aux prix de l'année précédente, séries chaînées

G2002/09 F. HILD

Les soldes d'opinion résument-ils au mieux les réponses des entreprises aux enquêtes de conjoncture ?

G2002/10 I. ROBERT-BOBÉE

Les comportements démographiques dans le modèle de microsimulation Destinie - Une comparaison des estimations issues des enquêtes Jeunes et Carrières 1997 et Histoire Familielle 1999

G2002/11 J.-P. ZOYEM

La dynamique des bas revenus : une analyse des entrées-sorties de pauvreté

G2002/12 F. HILD

Prévisions d'inflation pour la France

G2002/13 M. LECLAIR

Réduction du temps de travail et tensions sur les facteurs de production

G2002/14 E. WALRAET - A. VINCENT

- Analyse de la redistribution intragénérationnelle dans le système de retraite des salariés du privé - Une approche par microsimulation

- Intragenerational distributional analysis in the french private sector pension scheme - A microsimulation approach

G2002/15 P. CHONE - D. LE BLANC - I. ROBERT-BOBEE

Offre de travail féminine et garde des jeunes enfants

G2002/16 F. MAUREL - S. GREGOIR

Les indices de compétitivité des pays : inter-prétation et limites

G2003/01 N. RIEDINGER - E. HAUVY

Le coût de dépollution atmosphérique pour les entreprises françaises : Une estimation à partir de données individuelles

G2003/02 P. BISCOURP et F. KRAMARZ

Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises : une analyse sur la période 1986-1992

G2003/03 Bilan des activités de la DESE - 2002

G2003/04 P.-O. BEFFY - J. DEROYON -

N. FOURCADE - S. GREGOIR - N. LAÎB - B. MONFORT

Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020

G2003/05 P. AUBERT

La situation des salariés de plus de cinquante ans dans le secteur privé

G2003/06 P. AUBERT - B. CRÉPON

Âge, salaire et productivité

La productivité des salariés décline-t-elle en fin de carrière ?

G2003/07 H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU

Le ralentissement de la productivité du travail au cours des années 1990

G2003/08 P.-O. BEFFY - B. MONFORT

Patrimoine des ménages, dynamique d'allocation et comportement de consommation

G2003/09 P. BISCOURP - N. FOURCADE

Peut-on mettre en évidence l'existence de rigidités à la baisse des salaires à partir de données individuelles ? Le cas de la France à la fin des années 90

G2003/10 M. LECLAIR - P. PETIT

Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes ?

G2003/11 P.-O. BEFFY - X. BONNET - M. DARRACQ-PARIES - B. MONFORT

MZE: a small macro-model for the euro area

G2004/01 P. AUBERT - M. LECLAIR

La compétitivité exprimée dans les enquêtes trimestrielles sur la situation et les perspectives dans l'industrie

G2004/02 M. DUÉE - C. REBILLARD

La dépendance des personnes âgées : une projection à long terme

G2004/03 S. RASPILLER - N. RIEDINGER

Régulation environnementale et choix de localisation des groupes français

G2004/04 A. NABOULET - S. RASPILLER

Les déterminants de la décision d'investir : une approche par les perceptions subjectives des firmes

G2004/05 N. RAGACHE

La déclaration des enfants par les couples non mariés est-elle fiscalement optimale ?

G2004/06 M. DUÉE

L'impact du chômage des parents sur le devenir scolaire des enfants

G2004/07 P. AUBERT - E. CAROLI - M. ROGER

New Technologies, Workplace Organisation and the Age Structure of the Workforce: Firm-Level Evidence

G2004/08 E. DUGUET - C. LELARGE

Les brevets accroissent-ils les incitations privées à innover ? Un examen microéconomique

G2004/09 S. RASPILLER - P. SILLARD

Affiliating versus Subcontracting: the Case of Multinationals

G2004/10 J. BOISSINOT - C. L'ANGEVIN - B. MONFORT

Public Debt Sustainability: Some Results on the French Case

G2004/11 S. ANANIAN - P. AUBERT

Travailleurs âgés, nouvelles technologies et changements organisationnels : un réexamen à partir de l'enquête « REPONSE »

G2004/12 X. BONNET - H. PONCET

Structures de revenus et propensions différentes à consommer - Vers une équation de consommation des ménages plus robuste en prévision pour la France

G2004/13 C. PICART

Évaluer la rentabilité des sociétés non financières

G2004/14 J. BARDAJI - B. SÉDILLOT - E. WALRAET

Les retraites du secteur public : projections à l'horizon 2040 à l'aide du modèle de microsimulation DESTINIE

G2005/01 S. BUFFETEAU - P. GODEFROY

Conditions de départ en retraite selon l'âge de fin d'études : analyse prospective pour les générations 1945 a1974

G2005/02 C. AFSA - S. BUFFETEAU

L'évolution de l'activité féminine en France : une approche par pseudo-panel

G2005/03 P. AUBERT - P. SILLARD

Délocalisations et réductions d'effectifs dans l'industrie française

G2005/04 M. LECLAIR - S. ROUX

Mesure et utilisation des emplois instables dans les entreprises

G2005/05 C. L'ANGEVIN - S. SERRAVALLE

Performances à l'exportation de la France et de l'Allemagne - Une analyse par secteur et destination géographique

G2005/06 Bilan des activités de la Direction des Études et Synthèses Economiques - 2004

G2005/07 S. RASPILLER

La concurrence fiscale : principaux enseignements de l'analyse économique

G2005/08 C. L'ANGEVIN - N. LAÎB

Éducation et croissance en France et dans un panel de 21 pays de l'OCDE

G2005/09 N. FERRARI

Prévoir l'investissement des entreprises
Un indicateur des révisions dans l'enquête de conjoncture sur les investissements dans l'industrie.
G2005/10 P.-O. BEFFY - C. L'ANGEVIN
Chômage et boucle prix-salaires : apport d'un modèle « qualifiés/peu qualifiés »

G2005/11 B. HEITZ
A two-states Markov-switching model of inflation in France and the USA: credible target VS inflation spiral

G2005/12 O. BIAU - H. ERKEL-ROUSSE - N. FERRARI
Réponses individuelles aux enquêtes de conjoncture et prévision macroéconomiques : Exemple de la prévision de la production manufacturière

G2005/13 P. AUBERT - D. BLANCHET - D. BLAU
The labour market after age 50: some elements of a Franco-American comparison

G2005/14 D. BLANCHET - T. DEBRAND - P. DOUGRON - P. POLLET
L'enquête SHARE : présentation et premiers résultats de l'édition française

G2005/15 M. DUÉE
La modélisation des comportements démographiques dans le modèle de microsimulation DESTINIE

G2005/16 H. RAOUI - S. ROUX
Étude de simulation sur la participation versée aux salariés par les entreprises

G2006/01 C. BONNET - S. BUFFETEAU - P. GODEFROY
Disparités de retraite de droit direct entre hommes et femmes : quelles évolutions ?

G2006/02 C. PICART
Les gazelles en France

G2006/03 P. AUBERT - B. CRÉPON - P. ZAMORA
Le rendement apparent de la formation continue dans les entreprises : effets sur la productivité et les salaires

G2006/04 J.-F. OUVRARD - R. RATHELOT
Demographic change and unemployment: what do macroeconometric models predict?

G2006/05 D. BLANCHET - J.-F. OUVRARD
Indicateurs d'engagements implicites des systèmes de retraite : chiffrages, propriétés analytiques et réactions à des chocs démographiques types

G2006/06 G. BIAU - O. BIAU - L. ROUVIERE
Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data

G2006/07 C. AFSA - P. GIVORD
Le rôle des conditions de travail dans les absences pour maladie

G2006/08 P. SILLARD - C. L'ANGEVIN - S. SERRAVALLE
Performances comparées à l'exportation de la France et de ses principaux partenaires
Une analyse structurelle sur 12 ans

G2006/09 X. BOUTIN - S. QUANTIN
Une méthodologie d'évaluation comptable du coût du capital des entreprises françaises : 1984-2002

G2006/10 C. AFSA
L'estimation d'un coût implicite de la pénibilité du travail chez les travailleurs âgés

G2006/11 C. LELARGE
Les entreprises (industrielles) françaises sont-elles à la frontière technologique ?

G2006/12 O. BIAU - N. FERRARI
Théorie de l'opinion
Faut-il pondérer les réponses individuelles ?

G2006/13 A. KOUBI - S. ROUX
Une réinterprétation de la relation entre productivité et inégalités salariales dans les entreprises

G2006/14 R. RATHELOT - P. SILLARD
The impact of local taxes on plants location decision

G2006/15 L. GONZALEZ - C. PICART
Diversification, centrage et poids des activités de support dans les groupes (1993-2000)

G2007/01 D. SRAER
Allègements de cotisations patronales et dynamique salariale

G2007/02 V. ALBOUY - L. LEQUIEN
Les rendements non monétaires de l'éducation : le cas de la santé

G2007/03 D. BLANCHET - T. DEBRAND
Aspiration à la retraite, santé et satisfaction au travail : une comparaison européenne

G2007/04 M. BARLET - L. CRUSSON
Quel impact des variations du prix du pétrole sur la croissance française ?

G2007/05 C. PICART
Flux d'emploi et de main-d'œuvre en France : un réexamen

G2007/06 V. ALBOUY - C. TAVAN
Massification et démocratisation de l'enseignement supérieur en France

G2007/07 T. LE BARBANCHON
The Changing response to oil price shocks in France: a DSGE type approach

G2007/08 T. CHANEY - D. SRAER - D. THESMAR
Collateral Value and Corporate Investment Evidence from the French Real Estate Market

G2007/09 J. BOISSINOT
Consumption over the Life Cycle: Facts for France

G2007/10 C. AFSA
Interpréter les variables de satisfaction : l'exemple de la durée du travail

G2007/11 R. RATHELOT - P. SILLARD
Zones Franches Urbaines : quels effets sur l'emploi salarié et les créations d'établissements ?

G2007/12 V. ALBOUY - B. CRÉPON
Aléa moral en santé : une évaluation dans le cadre du modèle causal de Rubin

G2008/01 C. PICART
Les PME françaises : rentables mais peu dynamiques

G2008/02 P. BISCOURP - X. BOUTIN - T. VERGÉ
The Effects of Retail Regulations on Prices Evidence form the Loi Galland

G2008/03 Y. BARBESOL - A. BRIANT
Économies d'agglomération et productivité des entreprises : estimation sur données individuelles françaises

G2008/04 D. BLANCHET - F. LE GALLO
Les projections démographiques : principaux mécanismes et retour sur l'expérience française

G2008/05 D. BLANCHET - F. TOUTLEMONDE
Évolutions démographiques et déformation du cycle de vie active : quelles relations ?

G2008/06 M. BARLET - D. BLANCHET - L. CRUSSON
Internationalisation et flux d'emplois : que dit une approche comptable ?

G2008/07 C. LELARGE - D. SRAER - D. THESMAR
Entrepreneurship and Credit Constraints - Evidence from a French Loan Guarantee Program

G2008/08 X. BOUTIN - L. JANIN
Are Prices Really Affected by Mergers?

G2008/09 M. BARLET - A. BRIANT - L. CRUSSON
Concentration géographique dans l'industrie manufacturière et dans les services en France : une approche par un indicateur en continu

G2008/10 M. BEFFY - É. COUDIN - R. RATHELOT
Who is confronted to insecure labor market histories? Some evidence based on the French labor market transition

G2008/11 M. ROGER - E. WALRAET
Social Security and Well-Being of the Elderly: the Case of France

G2008/12 C. AFSA
Analyser les composantes du bien-être et de son évolution
Une approche empirique sur données individuelles

G2008/13 M. BARLET - D. BLANCHET - T. LE BARBANCHON
Microsimplifier le marché du travail : un prototype

G2009/01 P.-A. PIONNIER
Le partage de la valeur ajoutée en France, 1949-2007

G2009/02 Laurent CLAVEL - Christelle MINODIER
A Monthly Indicator of the French Business Climate

G2009/03 H. ERKEL-ROUSSE - C. MINODIER
Do Business Tendency Surveys in Industry and Services Help in Forecasting GDP Growth? A Real-Time Analysis on French Data

G2009/04 P. GIVORD - L. WILNER
Les contrats temporaires : trappe ou marchepied vers l'emploi stable ?

G2009/05 G. LALANNE - P.-A. PIONNIER - O. SIMON
Le partage des fruits de la croissance de 1950 à 2008 : une approche par les comptes de surplus

G2009/06 L. DAVEZIES - X. D'HAULTFOEUILLE
Faut-il pondérer ?... Ou l'éternelle question de l'économètre confronté à des données d'enquête

G2009/07 S. QUANTIN - S. RASPILLER - S. SERRAVALLE
Commerce intragroupe, fiscalité et prix de transferts : une analyse sur données françaises

G2009/08 M. CLERC - V. MARCUS
Élasticités-prix des consommations énergétiques des ménages

G2009/09 G. LALANNE - E. POULIQUEN - O. SIMON
Prix du pétrole et croissance potentielle à long terme

G2009/10 D. BLANCHET - J. LE CACHEUX - V. MARCUS
Adjusted net savings and other approaches to sustainability: some theoretical background

G2009/11 V. BELLAMY - G. CONSALES - M. FESSEAU - S. LE LAIDIER - É. RAYNAUD
Une décomposition du compte des ménages de la comptabilité nationale par catégorie de ménage en 2003

G2009/12 J. BARDAJI - F. TALLET
Detecting Economic Regimes in France: a Qualitative Markov-Switching Indicator Using Mixed Frequency Data

G2009/13 R. AEBERHARDT - D. FOUGÈRE - R. RATHELOT

Discrimination à l'embauche : comment exploiter les procédures de testing ?

G2009/14 Y. BARBESOL - P. GIVORD - S. QUANTIN
Partage de la valeur ajoutée, approche par données microéconomiques

G2009/15 I. BUONO - G. LALANNE
The Effect of the Uruguay round on the Intensive and Extensive Margins of Trade

G2010/01 C. MINODIER
Avantages comparés des séries des premières valeurs publiées et des séries des valeurs révisées - Un exercice de prévision en temps réel de la croissance trimestrielle du PIB en France

G2010/02 V. ALBOUY - L. DAVEZIES - T. DEBRAND
Health Expenditure Models: a Comparison of Five Specifications using Panel Data

G2010/03 C. KLEIN - O. SIMON
Le modèle MÉSANGE réestimé en base 2000 Tome 1 – Version avec volumes à prix constants

G2010/04 M.-É. CLERC - É. COUDIN
L'IPC, miroir de l'évolution du coût de la vie en France ? Ce qu'apporte l'analyse des courbes d'Engel

G2010/05 N. CECI-RENAUD - P.-A. CHEVALIER
Les seuils de 10, 20 et 50 salariés : impact sur la taille des entreprises françaises

G2010/06 R. AEBERHARDT - J. POUGET
National Origin Differences in Wages and Hierarchical Positions - Evidence on French Full-Time Male Workers from a matched Employer-Employee Dataset

G2010/07 S. BLASCO - P. GIVORD
Les trajectoires professionnelles en début de vie active : quel impact des contrats temporaires ?

G2010/08 P. GIVORD
Méthodes économétriques pour l'évaluation de politiques publiques

G2010/09 P.-Y. CABANNES - V. LAPÈGUE - E. POULIQUEN - M. BEFFY - M. GAINI
Quelle croissance de moyen terme après la crise ?

G2010/10 I. BUONO - G. LALANNE
La réaction des entreprises françaises à la baisse des tarifs douaniers étrangers
G2010/11 R. RATHELOT - P. SILLARD
L'apport des méthodes à noyaux pour mesurer la concentration géographique - Application à la concentration des immigrés en France de 1968 à 1999

G2010/12 M. BARATON - M. BEFFY - D. FOUGÈRE
Une évaluation de l'effet de la réforme de 2003 sur les départs en retraite - Le cas des enseignants du second degré public

G2010/13 D. BLANCHET - S. BUFFETEAU - E. CRENNER
S. LE MINEZ
Le modèle de microsimulation Destinie 2 : principales caractéristiques et premiers résultats

G2010/14 D. BLANCHET - E. CRENNER
Le bloc retraites du modèle Destinie 2 : guide de l'utilisateur

G2010/15 M. BARLET - L. CRUSSON - S. DUPUCH - F. PUECH
Des services échangés aux services échangeables : une application sur données françaises

G2010/16 M. BEFFY - T. KAMIONKA
Public-private wage gaps: is civil-servant human capital sector-specific?

G2010/17 P.-Y. CABANNES - H. ERKEL-ROUSSE - G. LALANNE - O. MONSO - E. POULIQUEN
Le modèle Mésange réestimé en base 2000 Tome 2 - Version avec volumes à prix chaînés

G2010/18 R. AEBERHARDT - L. DAVEZIES
Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases

G2011/01 T. LE BARBANCHON - B. OURLIAC - O. SIMON
Les marchés du travail français et américain face aux chocs conjoncturels des années 1986 à 2007 : une modélisation DSGE

G2011/02 C. MARBOT
Une évaluation de la réduction d'impôt pour l'emploi de salariés à domicile

G2011/03 L. DAVEZIES
Modèles à effets fixes, à effets aléatoires, modèles mixtes ou multi-niveaux : propriétés et mises en œuvre des modélisations de l'hétérogénéité dans le cas de données groupées

G2011/04 M. ROGER - M. WASMER
Heterogeneity matters: labour productivity differentiated by age and skills

G2011/05 J.-C. BRICONGNE - J.-M. FOURNIER
V. LAPÈGUE - O. MONSO
De la crise financière à la crise économique L'impact des perturbations financières de 2007 et 2008 sur la croissance de sept pays industrialisés

G2011/06 P. CHARNOZ - É. COUDIN - M. GAINI
Wage inequalities in France 1976-2004: a quantile regression analysis

G2011/07 M. CLERC - M. GAINI - D. BLANCHET
Recommendations of the Stiglitz-Sen-Fitoussi Report: A few illustrations

G2011/08 M. BACHELET - M. BEFFY - D. BLANCHET
Projet l'impact des réformes des retraites sur l'activité des 55 ans et plus : une comparaison de trois modèles

G2011/09 C. LOUVOT-RUNAVOT
L'évaluation de l'activité dissimulée des entre-

prises sur la base des contrôles fiscaux et son insertion dans les comptes nationaux

G2011/10 A. SCHREIBER - A. VICARD
La tertiairisation de l'économie française et le ralentissement de la productivité entre 1978 et 2008

G2011/11 M.-É. CLERC - O. MONSO - E. POULIQUEN
Les inégalités entre générations depuis le baby-boom

G2011/12 C. MARBOT - D. ROY
Évaluation de la transformation de la réduction d'impôt en crédit d'impôt pour l'emploi de salariés à domicile en 2007

G2011/13 P. GIVORD - R. RATHELOT - P. SILLARD
Place-based tax exemptions and displacement effects: An evaluation of the Zones Franches Urbaines program

G2011/14 X. D'HAULTFOEUILLE - P. GIVORD - X. BOUTIN
The Environmental Effect of Green Taxation: the Case of the French "Bonus/Malus"

G2011/15 M. BARLET - M. CLERC - M. GARNEO - V. LAPÈGUE - V. MARCUS
La nouvelle version du modèle MZE, modèle macroéconomique pour la zone euro

G2011/16 R. AEBERHARDT - I. BUONO - H. FADINGER
Learning, Incomplete Contracts and Export Dynamics: theory and Evidence form French Firms

G2011/17 C. KERDRAIN - V. LAPÈGUE
Restrictive Fiscal Policies in Europe: What are the Likely Effects?

G2012/01 P. GIVORD - S. QUANTIN - C. TREVIEN
A Long-Term Evaluation of the First Generation of the French Urban Enterprise Zones

G2012/02 N. CECI-RENAUD - V. COTTET
Politique salariale et performance des entreprises

G2012/03 P. FÉVRIER - L. WILNER
Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior

G2012/04 M. GAINI - A. LEDUC - A. VICARD
School as a shelter? School leaving-age and the business cycle in France

G2012/05 M. GAINI - A. LEDUC - A. VICARD
A scarred generation? French evidence on young people entering into a tough labour market

G2012/06 P. AUBERT - M. BACHELET
Disparités de montant de pension et redistribution dans le système de retraite français

G2012/07 R. AEBERHARDT - P GIVORD - C. MARBOT
Spillover Effect of the Minimum Wage in France: An Unconditional Quantile Regression Approach

G2012/08 A. EIDELMAN - F. LANGUMIER - A. VICARD
Prélèvements obligatoires reposant sur les ménages : des canaux redistributifs différents en 1990 et 2010

G2012/09 O. BARGAIN - A. VICARD
Le RMI et son successeur le RSA découragent-ils certains jeunes de travailler ? Une analyse sur les jeunes autour de 25 ans

G2012/10 C. MARBOT - D. ROY
Projections du coût de l'APA et des caractéristiques de ses bénéficiaires à l'horizon 2040 à l'aide du modèle Destinie

G2012/11 A. MAUROUX
Le crédit d'impôt dédié au développement durable : une évaluation économique

G2012/12 V. COTTET - S. QUANTIN - V. RÉGNIER
Coût du travail et allègements de charges : une estimation au niveau établissement de 1996 à 2008

G2012/13 X. D'HAULTFOEUILLE - P. FÉVRIER - L. WILNER
Demand Estimation in the Presence of Revenue Management

G2012/14 D. BLANCHET - S. LE MINEZ
Joint macro/micro evaluations of accrued-to-date pension liabilities: an application to French reforms

G2013/01 T. DEROYON - A. MONTAUT - P-A PIONNIER
Utilisation rétrospective de l'enquête Emploi à une fréquence mensuelle : apport d'une modélisation espace-état

G2013/02 C. TREVIEN
Habiter en HLM : quel avantage monétaire et quel impact sur les conditions de logement ?

G2013/03 A. POISSONNIER
Temporal disaggregation of stock variables - The Chow-Lin method extended to dynamic models

G2013/04 P. GIVORD - C. MARBOT
Does the cost of child care affect female labor market participation? An evaluation of a French reform of childcare subsidies

G2013/05 G. LAME - M. LEQUIEN - P.-A. PIONNIER
Interpretation and limits of sustainability tests in public finance

G2013/06 C. BELLEGO - V. DORTET-BERNADET
La participation aux pôles de compétitivité : quelle incidence sur les dépenses de R&D et l'activité des PME et ETI ?

G2013/07 P.-Y. CABANNES - A. MONTAUT - P-A. PIONNIER
Évaluer la productivité globale des facteurs en France : l'apport d'une mesure de la qualité du capital et du travail

G2013/08 R. AEBERHARDT - C. MARBOT
Evolution of Instability on the French Labour Market During the Last Thirty Years

G2013/09 J-B. BERNARD - G. CLÉAUD
Oil price: the nature of the shocks and the impact on the French economy

G2013/10 G. LAME
Was there a « Greenspan Conundrum » in the Euro area?

G2013/11 P. CHONÉ - F. EVAIN - L. WILNER - E. YILMAZ
Introducing activity-based payment in the hospital industry : Evidence from French data

G2013/12 C. GRISLAIN-LETRÉMY
Natural Disasters: Exposure and Underinsurance

G2013/13 P.-Y. CABANNES - V. COTTET - Y. DUBOIS - C. LELARGE - M. SICSIC
French Firms in the Face of the 2008/2009 Crisis

G2013/14 A. POISSONNIER - D. ROY
Households Satellite Account for France in 2010. Methodological issues on the assessment of domestic production

G2013/15 G. CLÉAUD - M. LEMOINE - P.-A. PIONNIER
Which size and evolution of the government expenditure multiplier in France (1980-2010)?

G2014/01 M. BACHELET - A. LEDUC - A. MARINO
Les biographies du modèle Destinie II : rebasage et projection

G2014/02 B. GARBINTI
L'achat de la résidence principale et la création d'entreprises sont-ils favorisés par les donations et héritages ?

G2014/03 N. CECI-RENAUD - P. CHARNOZ - M. GAINI
Évolution de la volatilité des revenus salariaux du secteur privé en France depuis 1968

G2014/04 P. AUBERT
Modalités d'application des réformes des retraites et prévisibilité du montant de pension

G2014/05 C. GRISLAIN-LETRÉMY - A. KATOSSKY
The Impact of Hazardous Industrial Facilities on Housing Prices: A Comparison of Parametric and Semiparametric Hedonic Price Models

G2014/06 J.-M. DAUSSIN-BENICHOU - A. MAUROUX
Turning the heat up. How sensitive are households to fiscal incentives on energy efficiency investments?

G 2014 / 07 C. LABONNE - G. LAMÉ
Credit Growth and Capital Requirements: Binding or Not?