# Do Consumers Correctly Expect Price Reductions?
## Testing Dynamic Behavior

Philippe Février, Lionel Wilner

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Direction des Études et Synthèses Économiques

G 2012 / 03

# Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior

Philippe FÉVRIER et Lionel WILNER

Document de travail

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Institut National de la Statistique et des Études Économiques
INSTITUT NATIONAL DE LA STATISTIQUE ET DES ÉTUDES ÉCONOMIQUES

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

G 2012 / 03

Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior

Philippe FÉVRIER* - Lionel WILNER**

MARS 2012

Les auteurs remercient Christian BONTEMPS, Xavier D'HAULTFOEUILLE, Éric DUBOIS, Pauline GIVORD, Gautam GOWRISANKARAN, Johan HOMBERT, Claire LELARGE, Corinne PROST et Michael VISSER pour leurs suggestions, et les participants aux séminaires INSEE-D3E et CREST-LEI ainsi qu'aux conférences EARIE, EEA, ESWC, IIOC pour leurs commentaires. Toutes les erreurs restantes sont les nôtres.

<footnote>* CREST-LEI - 15, bd Gabriel Péri - 92245 MALAKOFF CEDEX</footnote>

<footnote>** Département des Études Économiques d'Ensemble - Division « Marchés et Stratégies d'Entreprise »
Timbre G230 - 15, bd Gabriel Péri - BP 100 - 92244 MALAKOFF CEDEX</footnote>
# Do Consumers Correctly Expect Price Reductions?
## Testing Dynamic Behavior

**Abstract**

The literature on both theoretical and empirical dynamics requires agents to solve complex dynamic programs, which assumes implicitly that agents are fully rational and have the most accurate expectations given their information set. We claim that this assumption is easily testable provided that market-level data on prices and purchases are available. Using data on albums exhibiting frequent episodes of promotions, we perform a test derived from the predictions of a simple demand model and find that consumers hold simple expectations on the timing of promotions: everything happens as if consumers were expecting a Markov price process. Our results are consistent with the idea that the rationality of consumers is bounded because of limited memory or limited capacity. These results have important implications in terms of demand estimation, firms' optimal pricing strategy and computation of the welfare.

**Keywords:** Testing expectations, dynamic behavior, sales, imperfect information, bounded rationality

## Les consommateurs anticipent-ils correctement les promotions ? Un test de comportement dynamique

**Résumé**

Dans la littérature à la fois empirique et théorique, les agents économiques résolvent des programmes dynamiques complexes, étant donné leur ensemble d'information, ce qui suppose implicitement que les agents sont entièrement rationnels et forment les anticipations appropriées. Nous mettons en avant l'idée que cette hypothèse est testable sur données détaillées au niveau d'un marché, comportant prix et volumes des ventes. A l'aide de données sur des œuvres musicales exhibant de fréquents épisodes avec des promotions, nous testons les prédictions d'un modèle de demande et trouvons que les consommateurs forment des anticipations simples au sujet du processus de prix : tout se passe comme si les consommateurs s'attendaient à un processus de prix de type Markov d'ordre 1. Ces résultats sont cohérents avec l'idée d'une rationalité limitée des agents, en raison d'une mémoire ou d'une capacité limitée. Ils ont des conséquences importantes en termes d'estimation de la demande, de la stratégie optimale de prix et de mesure du bien-être sur un marché.

**Mots-clés:** Test des anticipations, comportement dynamique, promotions, information imparfaite, rationalité limitée
# 1 Introduction

The importance of taking agents' dynamic behavior into account has been well em-
phasized by the theoretical literature on industrial organization. It is for instance often
assumed that consumers anticipate future prices and behave strategically. For instance,
Stokey (1981) requires consumers to be perfectly forward-looking in order to construct
the unique perfect equilibrium that leads to the Coasian outcome. Similarly, a growing
empirical literature on industrial organization has investigated the estimation of games
in which agents are fully rational and dynamic: seminal contributions include Aguirre-
gabiria and Mira (2007), Bajari et al. (2007), Pesendorfer and Schmidt-Dengler (2008).
Nair (2007) and Esteban and Shum (2007) also derive an intertemporal demand model
from an exact dynamic optimization program based on the assumption that agents are
perfectly forward-looking.

Though many of these papers make the assumption of full rationality, this is rather
demanding in a dynamic setting since it requires agents to hold correct expectations
over the future. Other papers estimating structural models of demand like Hendel and
Nevo (2006) and Gowrisankaran and Rysman (2011) assume that consumers are fully
rational but that the firm fixes prices according to some Markov process. Note that
this estimated demand is similar to the one estimated under a different assumption,
namely that the firm fixes prices optimally but that consumers expect a Markov process.
However, the derivation of optimal prices and the computation of the welfare would be
different, since a game in which both the firm and consumers behave optimally differs
from a game in which a fully rational firm faces non fully rational consumers; equilibrium
prices as well as purchases and profits are not the same. In a recent paper, Hendel and
Nevo (2011) posit several hypotheses about consumers' expectations, perfect foresight
as opposed to rational expectations, and estimate a model of demand under different
assumptions. They find that consumers are heterogeneous in their ability to store and
in their price-sensitivity.

This paper argues that the nature of consumers’ expectations is testable and proposes
a simple method to determine whether consumers hold correct beliefs or not for a specific
good. To this purpose, we exploit price variations to infer the nature of consumers’
behavior since accumulation, perfect foresight, myopic behavior or expectations based
on time-independent information sets shall correspond to distinct patterns of demand.

First, we claim that the availability of market-level data of prices and purchases is suf-
ficient to perform the test before the estimation of any structural model. To understand
how consumers form their expectations about the price process, we need to observe how
the demand reacts to some price change. We recognize that markets with highly volatile
prices are not suited to such an analysis since it would be hard to disentangle the price
effect from what is due to expectations. However, markets with sticky prices with occasional price changes (for instance, promotions) are appropriate to perform such a test. Intuitively, the pattern of demand should decrease when a price reduction approaches if consumers hold correct expectations, while it should stay flat otherwise. Facing firms that cut prices occasionally, consumers with correct expectations should anticipate that a sale is more and more likely to occur as time goes by and the price remains high. This prediction is quite strong since it holds as soon as at least some fraction of the population has some information at her disposal and is able to use it for making her decision.

Second, we perform the test using data on albums that exhibit occasional price reductions (sales or durable price changes) and find, though non-surprisingly, that consumers do not have correct expectations about prices in this market. However, consumers do take dynamic decisions since they cumulate and do wait for a lower price, but make mistakes about the schedule of price reductions. We find that the pattern of purchases is essentially flat before a price reduction while the price stays constantly high, which indicates that consumers are rather naive. Besides, the myopic hypothesis is ruled out: we find evidence that consumers postpone their decision of purchase and wait for a lower price. We conclude that consumers are aware of promotions and wait for them, but have seemingly a wrong timing in mind or form “simple” expectations, that they do not update accordingly as time goes by. They behave as if the firm was setting prices as a function of lagged prices only. On the contrary, the firm looks strategic enough and does not set prices according to this simple process: the timing of promotions is found to depend on the duration since the last one. In this market, it would be more appropriate to assume that the firm is rather fully rational with perfect foresight while consumers have simpler expectations.

These aspects are important and play a key role, especially when dynamic decisions are involved. The rationality assumption is quite demanding in such settings: consumers are required not only to optimize but also to form correct expectations over future sequences of prices given their past information. In particular, not only preferences matter but also *perceived opportunities* (Vriend (1996)) that include all relevant information for the consumer's choice. The rational expectations hypothesis (Muth (1961), Lucas (1995)) states that agents collect relevant information and anticipate correctly the whole price path. An exhaustive empirical literature aims at testing this assumption; results depend on economic issues that are considered. Much attention has been devoted to price processes, which is especially relevant for macroeconomics to assess whether perceived inflation coincides or not with the actual rate. Famous examples of tests include Lucas (1972), Sargent et al. (1973) and Barro (1977).

The psychological literature tends to argue that consumers expectations may not be perfect because of intrinsic limitations. Turnovsky (1970) and Lovell (1986) bring em-
pirical evidence that casts doubts on the validity of the rational expectations hypothesis. According to Manski (2004), the coincidence between subjective beliefs and objective probabilities is an extreme assumption that is not likely to hold for most agents. Clerides and Courty (2010) bring also evidence of consumer inattention by looking at sales.

However, concerning income distributions, Dominitz and Manski (1997) find that subjective perceptions are close to actual distributions. Looking at life expectancy, Hamermesh (1985) as well as Hurd and McGarry (2002) show that individual beliefs are consistent with the rational expectations hypothesis: older people have higher subjective life expectancies and people take the past into account in forming their expectations.

The paper is organized as follows. In the next section, we expose a simple model that explains how expectations can be recovered from the observation of demand. Section 3 presents the data we use. Section 4 documents the strategy used by the firm and especially the fact that sales are predictable. Section 5 is devoted to the test of consumers expectations and Section 6 discusses our results with respect to the firm's strategic and dynamic behavior. Section 7 concludes.

## 2 Dynamic demand and consumer expectations

In this section, we explain what can be learned from the demand observation of a durable good about consumer expectations when a firm uses sticky prices with a regular price and occasional sales at a lower price. To capture all the intuitions, we consider a discrete time setting and suppose that the firm charges a high price $\bar{p}$ during $n$ periods and cuts prices at $n+1$ to $\underline{p} < \bar{p}$. The sale lasts several periods, say $s$, and such cycles repeat over time. We will show that this simple framework enables us to discriminate between different kind of information used by consumers to form their expectations.

More precisely, we suppose that the demand comes from impatient consumers who discount the future at factor $\delta \in [0; 1]$. These consumers are heterogeneous among their valuation $v \in [0; +\infty[$ distributed according to some cdf $F(\cdot)$. Their current utility at $t$ writes $v - p_t$. Every period new identical cohorts of consumers arrive in the market with a mass normalized at one whereas old cohorts of consumers remain in the market until the next period with probability $\alpha \in [0; 1]$. The timing is thus the following: at the beginning of period $t$, a new cohort arrives and joins consumers who remain in the market, all consumers observe prices and the demand is formed. People who do not purchase either drop out or remain in the market until period $t+1$.

Dynamics is at stake only if some consumers remain in the market i.e $\alpha > 0$. Indeed, when $\alpha = 0$, we face a repeated static game. Regardless of their expectations, buyers in period $t$ are new consumers whose valuation is higher than the current price. The
<figure><img src="image_3.png" /><figcaption>Figure 1: No accumulation</figcaption></figure>

demand is equal to $1 - F(\bar{p})$ when the price is high and to $1 - F(p)$ when the price is low. This yields to flat patterns of purchases as described by Figure 1. On the contrary, when $\alpha > 0$, the pattern of purchases depends on consumers' expectations about prices and sales.

## 2.1 Perfect foresight or imperfect and time dependent information

We first suppose that consumers have perfect foresight regarding prices. This means that they perfectly anticipate that the firm uses price cycles and perfectly know where they are in that cycle. In period $t = 1, ..., n$, a consumer with valuation $v$ buys if and only if

$$v - \bar{p} \geq (\alpha\delta)^{n-t+1}(v - \underline{p}) \quad (1)$$

that is

$$v \geq v_n(t) \equiv \frac{\bar{p} - (\alpha\delta)^{n-t+1}\underline{p}}{1 - (\alpha\delta)^{n-t+1}} = \bar{p} + \frac{(\alpha\delta)^{n-t+1}}{1 - (\alpha\delta)^{n-t+1}}(\bar{p} - \underline{p})$$

Because $v_n(t)$ is increasing with time $t$, the demand, given by $1 - F(v_n(t))$, decreases with $t$. This result is quite intuitive: as time goes by, the date of the sale is approaching and more and more consumers wait for the sale. This effect induces a declining pattern of purchases over time when the price is high. This declining pattern is the dual of the declining pattern of prices described in Conlisk et al. (1984). They show that a firm facing consumers with discrete heterogenous valuations uses price cycles in which the price decreases. The firm wants high valuation consumers to purchase as soon as they enter the market and prices decrease to make them indifferent between purchasing
immediately or later on. The firm thus lower prices when a sale approaches and quantities are constant over time. Our point of view is exactly dual. Fixing the firm's strategy at a constant price during $n$ periods, purchases are decreasing to reflect that consumers are more likely to wait for the sale.

<figure><img src="image_4.png" /><figcaption>Figure 2: Accumulation and time dependent information</figcaption></figure>

More generally, this analysis indicates that the declining pattern should be observed not only if consumers perfectly foresight prices but also as soon as at least some consumers know that, as time $t$ goes by, the sale is closer and/or more likely to happen. Indeed, even with imperfect information, a declining pattern will arise as soon as consumers at time $t+1$ are aware, given their information set, that they have a greater incentive to wait than consumers at time $t$. We will say in that case that consumers face imperfect but time dependent information about the sales. Note finally that $v_n(t)$ and thus the current demand $q_t$ during high prices do not depend on $n$ but on the remaining time $n-t+1$ until the next sale.

We now turn to the pattern of purchases during sales. At the beginning of the sale, in period $n+1$, consumers of all cohorts are present in the market. Indeed, at the end of each period $t$, consumers whose valuations were lower than $v_n(t)$ but greater than $\underline{p}$ decided to wait for a sale. As they remain in the market until period $n+1$ with probability $\alpha^{n-t+1}$, there is a peak of demand at the beginning of the sale equal to

$$ \sum_{t=1}^{n} \alpha^{n-t+1}[F(v_n(t)) - F(\underline{p})] + 1 - F(\underline{p}). \quad (2) $$

This peak comes both from accumulation of low-valuation consumers and from strategic behavior implied by perfect expectations. It increases in particular when $n$ increases,
because more consumers have accumulated. During the rest of the sale, since the stock of consumers who were waiting for a low price had been emptying out in period $n+1$, the demand is made up only of new consumers. All new consumers with a valuation greater than $\underline{p}$ have an incentive to buy immediately and the demand is thus equal to $1 - F(\underline{p})$.

Figure 2 summarizes the pattern of demand that should be observed if consumers have perfect foresight regarding prices.

## 2.2 Myopic or uninformed consumers

Let's now turn to the case of myopic consumers who do not value the future: $\delta = 0$. The consumer decision is thus static and the consumer buys the good if and only if his valuation is above $\bar{p}$. Hence, the pattern of purchases is flat and equal to $1 - F(\bar{p})$ during a period with a high price. A similar pattern would also be observed with consumers who value the future but do not have any information about the prices used by the firm and thus only take their decision on the current price they observe. In both cases, the demand is flat and only depends on $\bar{p}$.

<figure><img src="image_5.png" /><figcaption>Figure 3: Accumulation and myopia</figcaption></figure>

Then, at the beginning of the sale, because consumers accumulate, we should observe a peak of demand given by

$$[F(\bar{p}) - F(\underline{p})]\alpha \frac{1 - \alpha^n}{1 - \alpha} + 1 - F(\underline{p}). \quad (3)$$

However, contrary to the previous case, the peak comes only from accumulation of low-valuation consumers but not from strategic delaying of purchases. Finally, once the stock of consumers is emptied out, the demand during the rest of the sale is flat and given by $1 - F(\underline{p})$. The whole pattern is depicted in Figure 3.
## 2.3 Imperfect and time independent information

Finally, we study an intermediate situation in which consumers have some information about the prices and sales used by the firm but do not take into account that, as time $t$ goes by, the sale is closer and/or more likely to happen. We say that consumers face imperfect and time independent information about the sales. This would be the case for instance if consumers do not know whether the last sale happened one week or one month ago even though they know that a sale occurs every quarter. As a result, they will assign some constant probability $\frac{1}{n}$ over time to each period $t = 1, ..., n$.

Their decision to purchase at time $t$ will thus be based on the intertemporal trade-off with respect to the $n$ future periods and consumers will buy the product if and only if:

$$v - \bar{p} \geq \sum_{\tau=t+1}^{t+n} \frac{1}{n}[(\alpha\delta)^{\tau-t}(v - \underline{p})] = \sum_{\tau'=1}^{n} (\alpha\delta)^{\tau'} \frac{v - \underline{p}}{n} \quad (4)$$

that is

$$v \geq w_n = \bar{p} + \frac{\frac{\alpha\delta}{n} \frac{1-(\alpha\delta)^n}{1-\alpha\delta}}{1 - \frac{\alpha\delta}{n} \frac{1-(\alpha\delta)^n}{1-\alpha\delta}} (\bar{p} - \underline{p}) \quad (5)$$

The corresponding pattern of purchases during periods with a high price is flat and the demand is $1 - F(w_n)$ where $w_n$ decreases with $n$. The peak at the beginning of the sale is equal to

$$[F(w_n) - F(\underline{p})]\alpha \frac{1 - \alpha^n}{1 - \alpha} + 1 - F(\underline{p})$$

whereas the demand during the rest of the sale is, as usual $1 - F(\underline{p})$.

A similar result is obtained if we suppose that consumers act as if there was a probability $\lambda = \frac{1}{n}$ that the album is on-sale at each period. Indeed, in that case, consumers would buy at $t$ if:

$$v - \bar{p} \geq (\alpha\delta) \left[ \left(1 - \frac{1}{n}\right) (v - \bar{p}) + \frac{1}{n} (v - \underline{p}) \right]$$

that is

$$v \geq w'_{n} = \bar{p} + \frac{\alpha\delta}{1 - \alpha\delta} \frac{1}{n} (\bar{p} - \underline{p}) \quad (6)$$

which leads to the same pattern than previously, as depicted in Figure 4.

Because the consumer information is time independent, $w_n$ and $w'_n$ do not depend on $t$ and we do not observe a declining pattern as in Figure 2. On the contrary, Figures 3 and 4 look qualitatively very similar with a flat demand when prices are high. Yet, the levels of the demand are very different. On one hand, myopic or uninformed consumers only take their decision on $\bar{p}$. On the other hand, $w_n$ and $w'_n$ do not only depend on $\bar{p}$ but
<figure><img src="image_6.png" /><figcaption>Figure 4: Accumulation and time independent information</figcaption></figure>

also vary with $p$ and $n$. The more attractive the sale appears, the smaller the demand is outside sale periods. The demand during high prices increases with the price during sales because the sale is less profitable. Similarly, when $n$ increases, the demand during high prices increases because a sale is less likely to occur. The characteristics of the sale influence the demand level but not the pattern of purchases when prices are high.

## 2.4 Predictions

Using the predictions of this basic model, we can first test if dynamics plays an important role in the market. To do so, we have to study the accumulation process.

**Prediction 1** *Dynamics is relevant and important if*

* The demand is higher at the beginning of the sale than at the end of it

* The demand at the beginning of the sale increases with $\bar{p}$, the price used off the sales

* The demand at the beginning of the sale increases with $n$, the time since the last sale

If dynamics is important, our simple model also provides conditions to test the nature of information used by consumers to form their expectations and take their decisions.

**Prediction 2** *If consumers either perfectly foresight the prices or use imperfect but time dependent information about the sales to form their expectations and take their decisions, the purchases should*
* decrease during periods when the price stays constantly high

* be greater after a sale than before it

* decrease with $p$, the price used off the sales

* increase with $p$ the price during the sale

* not depend on $n$, the time since the last sale

**Prediction 3** If consumers are either myopic or do not use any information about the sales to form their expectations and take their decisions, the demand during periods when the price stays constantly high should stay constant and not depend on anything but the current price.

**Prediction 4** If consumers use imperfect and time independent information about the sales to form their expectations and take their decisions, the demand during periods when the price stays constantly high should

* stay constant

* be similar after a sale and before it

* decrease with $p$, the price used off the sales

* increase with $p$ the price during the sale

* increase with $n$, the time since the last sale

## 3 Data

In France, the music industry is heavily concentrated: non-specialized superstores have an aggregated market share of 40%, as specialized superstores do, the rest of the sales being made by independents or other retailers. We have data from the most important French music retailer, selling 25% of albums and thus the main specialized chain with 62.5% of the market. Our working sample is made up of 121 records that are sold the most in its 10 major stores from January 2003 to November 2006. Six stores are located in Paris while the four remaining stores are in large French cities: Grenoble, Lille, Lyon and Toulouse. Our balanced panel has 245,630 observations; each observation corresponds to some record $j$ that was sold (or not) by store $r$ in week $t$ going from 1 to 203. For each observation some characteristics $X_j$ of the disc are available, including its author, its title and the name of its major (Sony, Warner, EMI...). We know how many albums were sold, i.e. the quantity $q_{jrt}$, and how much revenues $R_{jrt}$ these sales generated: prices are
<figure><img src="image_7.png" /><figcaption>Figure 5: Typical price and quantity patterns</figcaption></figure>
then computed from the ratio $\frac{R_{jrt}}{q_{jrt}}$. In the case where a disc was not sold however, i.e. when $q_{jrt} = 0$, the price is missing.

These albums come from the “world- and pop- music department” and were all released before 2001. This selection rules out new albums whose price strategies are specific to the introduction of a new good. As albums do not depreciate over time, and because consumers generally purchase an album at most once, these products are thought to be typical durable goods. Titles of most famous albums in our sample include for instance Nevermind (Nirvana), Platinum Collection (Queen), Doors (Doors), Led Zeppelin IV (Led Zeppelin), Parachutes (Coldplay), One (The Beatles), Andy Warhol (Velvet Underground), Wall (Pink Floyd). Appendix A provides the full list of albums.

An important issue comes from observations with no purchase: they account for 48% of the sample. In that case, when a price is missing, we follow a standard procedure to recover actual prices. Our method follows closely the one described by the Kilts Center for Marketing (Chicago Booth GSB) that provides publicly databases including data on ketchup like the one used by Pesendorfer (2002). The complete procedure is described in Appendix B.

These data provide information about the evolution of purchases and prices over time for every album-store. Price patterns look similar to those exhibited by Pesendorfer (2002) on ketchup brands: long periods of high prices with occasional price cut followed by a return to the previous price. Figure 5 displays typical joint patterns of prices and purchases. Specifically, there are two types of price changes: sales and durable price cuts, which we will first define and then describe.

## 3.1 Price reductions: sales and durable price changes

On the one hand, sales are occasional and may last from 3 to 8 weeks, with a discount that is on average about 30%. On the other hand, durable price changes correspond to the firm's fixing a new lower regular price. From Figure 5 for instance, we see that the price of the album “Greatest hits” by Janis Joplin falls frequently from 11.5 to 7.5 euros on sale but from August 2005, the regular price switches from 11.5 to 10.6 euros, while sales at 7.5 euros still occur. In that case, we have what we call a “durable price change”. Such changes shall not be disregarded in our analysis. According to Prediction 1, if consumers do not cumulate, a flat pattern must be observed after the price falls, while some (small) peak of demand should be observed otherwise. Furthermore, if consumers have correct expectations, they should anticipate this price fall.

We may observe several consecutive price reductions. In that case, we want to test for the anticipation behavior over the period that precedes the first price reduction, but for accumulation over every period with a lower price than the price before the first
price reduction, controlling for the fact that the price keeps on falling. Put differently, if consumers do cumulate, a peak of demand should be observed every time the price decreases.

Finally, we have also small price reductions that are temporary discounts – observed during 1 or 2 weeks – for regular shoppers and that correspond to the firm’s customer-oriented price policy. We observe 2,314 reductions of this type, for which the median discount is 9.3%. Thus, they are distinct from our object of interest, involving more substantial and durable price cuts.

For this bunch of reasons, we define any downward change in a “price level” as a “price reduction”. Price levels correspond to most frequent prices, taking inflation into account as Figure 5 shows. They are defined at the album-store level. We obtain for each album-store between 1 and 10 price levels during the whole period of observation, most of them having about six price levels.

<table><caption>Table 1: Prices</caption><thead><tr><th rowspan="3"></th><th colspan="2">Price level</th><th colspan="2">Number of prices</th></tr><tr><th>I</th><th>II</th><th>III</th><th>IV</th></tr><tr><th>Frequency</th><th>Cumulated</th><th>Frequency</th><th>Cumulated</th></tr></thead><tbody><tr><td>1</td><td>61.54</td><td>61.54</td><td>0.83</td><td>0.83</td></tr><tr><td>2</td><td>18.67</td><td>80.20</td><td>9.09</td><td>9.92</td></tr><tr><td>3</td><td>8.94</td><td>89.15</td><td>22.56</td><td>32.48</td></tr><tr><td>4</td><td>5.45</td><td>94.59</td><td>30.99</td><td>63.47</td></tr><tr><td>5</td><td>3.45</td><td>98.04</td><td>20.66</td><td>84.13</td></tr><tr><td>6</td><td>1.46</td><td>99.50</td><td>10.50</td><td>94.63</td></tr><tr><td>7 to 10</td><td>0.50</td><td>100.00</td><td>5.37</td><td>100.00</td></tr></tbody></table>

Table 1 actually shows that 95% of the time, one of the four highest prices is charged, which indicates that prices are very sticky. To anticipate, this piece of evidence claims in favor of price exogeneity since prices are not likely to be correlated to current idiosyncratic shocks: otherwise, the distribution of price levels would look much more uniform than the one displayed by Table 1, Column II.

To sum up, we will test consumers’ behavior on these “price reductions” corresponding either to a sale or a durable price change. Weeks before such price reductions shall be used to test the anticipation part, while weeks during those episodes shall be used for the accumulation part. Importantly, we focus on sequences of high prices followed by
(multiple) price reductions. Such sequences are defined by their end, i.e. by the moment when the price decreases.

<table><caption>Table 2: Durations of “high-price/low-price” sequences</caption><thead><tr><th></th><th>mean</th><th>std</th><th>min</th><th>max</th><th>med</th></tr></thead><tbody><tr><td>High price</td><td>30.1</td><td>27.3</td><td>3</td><td>169</td><td>21</td></tr><tr><td>Low price</td><td>10.0</td><td>11.4</td><td>3</td><td>115</td><td>7</td></tr><tr><td>Whole sequence</td><td>40.1</td><td>31.6</td><td>6</td><td>202</td><td>30</td></tr></tbody></table>

N = 2,833 sequences of high-price/low-price.

Durations are computed in weeks.

Note that it is essential to consider sequences that begin with a price equal to the highest price level in order to test for anticipation. Otherwise, any medium price level can be seen as a price reduction from the highest price level and a decreasing pattern coming from accumulation of consumers whose valuation lies between this price and the highest price level: in other words, such periods could mix both anticipation and accumulation. As a result, to keep the test as pure as possible, we restrict our attention to 2,833 sequences that are strictly speaking a “high-price/low-price”: if several consecutive price reductions occur after a period with the highest price level, we consider only the first one to avoid the previous problem. Finally, we must focus on such sequences that are fully observed, excluding those for which we don’t know exactly the beginning, in which case we ignore the duration of the “high-price” period (see Table 2). On those interior sequences, one can see that they typically last 40 weeks: 30 weeks with the highest price and 10 weeks with a smaller price, though there is some heterogeneity in these durations.

## 3.2 Prices during price reductions

Characteristics of sales can be found in Table 3. The average price on (resp. off) sale is 9.9 (resp. 16.2) euros, which yields a discount of about 40%. The typical sale lasts 5 weeks, which is the mode of durations, and every album-store is on sale about once a year. As Figure 5 shows, there is no clear seasonality in the timing of such promotions. On average, every week in every store, about 7.5% of albums are on-sale.

Characteristics of durable price changes can be found in Table 4. Contrary to sales, durable price changes last longer: about 22 weeks. They involve a discount that is somehow close to 35%. Furthermore, almost every album knows at least one durable price change, which indicates a tougher price competition, mainly related with the growing competition with Internet and the development of the peer-to-peer device.
<table><caption>Table 3: Sales</caption><thead><tr><th></th><th>mean</th><th>std</th><th>min</th><th>max</th><th>med</th></tr></thead><tbody><tr><td>Price (non-sale, in euros)</td><td>16.2</td><td>5.7</td><td>4.2</td><td>41.6</td><td>16.7</td></tr><tr><td>Price (on-sale, in euros)</td><td>9.9</td><td>4.9</td><td>2.5</td><td>36.7</td><td>7.5</td></tr><tr><td>Number of sales (per album-store)</td><td>4.0</td><td>2.3</td><td>0</td><td>11</td><td>4</td></tr><tr><td>Duration (weeks)</td><td>7.4</td><td>4.3</td><td>3</td><td>60</td><td>6</td></tr><tr><td>Time spent on sale (fraction, %)</td><td>14.6</td><td>9.3</td><td>0</td><td>49.3</td><td>13.8</td></tr><tr><td>Discount (%)</td><td>37.8</td><td>15.9</td><td>5.1</td><td>79.5</td><td>37.4</td></tr><tr><td>Revenues (fraction, %)</td><td>35.0</td><td>20.5</td><td>0</td><td>82.5</td><td>34.9</td></tr></tbody></table>

$N = 4,831 \text{ sales}$

<table><caption>Table 4: Durable price changes</caption><thead><tr><th></th><th>mean</th><th>std</th><th>min</th><th>max</th><th>med</th></tr></thead><tbody><tr><td>Price (euros)</td><td>11.4</td><td>4.7</td><td>5.0</td><td>36.7</td><td>10.6</td></tr><tr><td>Number of durable price changes (per album-store)</td><td>0.9</td><td>0.6</td><td>0</td><td>2</td><td>1</td></tr><tr><td>Duration (weeks)</td><td>21.9</td><td>22.2</td><td>3</td><td>115</td><td>13</td></tr><tr><td>Discount (%)</td><td>35.3</td><td>20.0</td><td>5.4</td><td>73.1</td><td>35.4</td></tr></tbody></table>

$N = 1,109 \text{ durable price changes}$

### 3.3 Purchases

Turning now to purchases, the number of albums sold varies from 0 to – coincidentally – 203 per week, store and album. From Table 5, the average quantity on (resp. off) sale is 7.14 (resp. 1.05). These figures are consistent with the literature devoted to sales: in this market, the demand is about 6.8 times higher during a promotion.

Going back to Figure 5, we observe a clear peak of purchases at the beginning of sales followed by a strongly decreasing pattern of demand, which claims in favor of accumulation. We will document this phenomenon more formally in the next section but we note already on Table 5 that the average quantity sold during a sale<fnref n="1" /> is 7.14 per week while it is 9.87 during the second week and still 8.68 on the third week. There seems to be a peak of demand at the beginning of sales which is about 9.4 times the usual demand, 1.05 album per week and per store. After the peak, purchases decrease until an

<footnote n="1">¹here are the statistics for sales only. The same could be done for durable price changes. More striking figures are obtained on sales.</footnote>
<table><caption>Table 5: Weekly purchases</caption><thead><tr><th></th><th>mean</th><th>std</th><th>min</th><th>max</th><th>med</th></tr></thead><tbody><tr><td>Quantity (non-sale)</td><td>1.05</td><td>2.30</td><td>0</td><td>91</td><td>0</td></tr><tr><td>One month after a sale</td><td>1.31</td><td>2.34</td><td>0</td><td>33</td><td>1</td></tr><tr><td>Two months after a sale</td><td>1.17</td><td>2.07</td><td>0</td><td>37</td><td>0</td></tr><tr><td>One month before a sale</td><td>1.11</td><td>2.93</td><td>0</td><td>72</td><td>0</td></tr><tr><td>Two months before a sale</td><td>1.04</td><td>2.37</td><td>0</td><td>72</td><td>0</td></tr><tr><td>Quantity (on-sale)</td><td>7.14</td><td>10.73</td><td>0</td><td>203</td><td>3</td></tr><tr><td>First week of sale</td><td>7.12</td><td>9.39</td><td>1</td><td>86</td><td>4</td></tr><tr><td>Second week of sale</td><td>9.87</td><td>13.10</td><td>1</td><td>146</td><td>5</td></tr><tr><td>Third week of sale</td><td>8.68</td><td>12.11</td><td>0</td><td>128</td><td>4</td></tr><tr><td>Tenth week of sale</td><td>4.07</td><td>7.94</td><td>0</td><td>107</td><td>2</td></tr></tbody></table>

Computations from 4,831 sales

average of 4.0 after 10 weeks<fnref n="1" />, which seems to rule out a flat pattern of purchases during a sale and suggests thus that consumers do cumulate. Since we aggregated daily data at a weekly level, the first week at the beginning of a sale necessarily mixes few days with a high price and the rest of the week with a low price, which explains that the average quantity sold during such a week is smaller than on the second week, consistently with the results of the next section.

Another argument in favor of accumulation is provided by Table 6. First, comparing columns of Table 6 suggests the existence of a decreasing pattern of purchases during price reductions, since the average level of purchases is higher at the beginning than at the end of price reductions. Second, comparing now rows, the longer the duration of the period with a high price before a price reduction – *n* in the model of section 2 –, the higher the peak of demand at the beginning of the price reduction: the difference previously mentioned increases from 1.32 when *n* is small to 2.76 when *n* is large. When *n* is small, about 8 albums are sold at the beginning of sales, while 14 albums are sold when *n* is higher: this large and significant difference seems to account for accumulation. However, these descriptive statistics do not control for the discount effect: for a given *n*, the peak of demand is higher if the price on sale is lower. Such effects, as well as time effects, have to be controlled for, and that is the reason why we proceed to the econometric test in the next section.

In the same vein, and still having a careful look at Table 5, we do not see any strong decreasing pattern of the demand during weeks when the price is high. Indeed, the

<footnote n="1">¹if any, since sales generally last less than 10 weeks</footnote>
<table><caption>Table 6: Weekly purchases during price reductions</caption><thead><tr><th rowspan="3"></th><th colspan="3">average nb of purchases</th><th>diff</th></tr><tr><th>first two weeks</th><th>first month</th><th>whole price reduction</th><th>I-III</th></tr><tr><th>I</th><th>II</th><th>III</th><th>IV</th></tr></thead><tbody><tr><th>n &lt; 10 weeks</th><td>7.83<br>(0.51)</td><td>7.74<br>(0.52)</td><td>6.51<br>(0.41)</td><td>1.32<br>(0.65)</td></tr><tr><th>10 &le; n &lt; 20 weeks</th><td>7.94<br>(0.37)</td><td>7.97<br>(0.40)</td><td>6.64<br>(0.34)</td><td>1.30<br>(0.50)</td></tr><tr><th>20 &le; n &lt; 30 weeks</th><td>10.37<br>(0.56)</td><td>9.91<br>(0.54)</td><td>8.05<br>(0.43)</td><td>2.32<br>(0.71)</td></tr><tr><th>30 &le; n &lt; 40 weeks</th><td>14.25<br>(0.68)</td><td>14.17<br>(0.66)</td><td>11.49<br>(0.53)</td><td>2.76<br>(0.86)</td></tr></tbody></table>

Note: *n* is the elapsed time between previous and current price reduction

average quantity is 1.11 during such periods while it is 1.31 (resp. 1.17) one month (resp. two months) after a sale and 1.11 one month before (resp. 1.04 two months before), with small and erratic variations week after week; these differences are not significant at the usual 5% level and claim in favor of a flat pattern during periods with high prices.

## 3.4 Heterogeneity

An analysis of variance indicates that an important part of the price dispersion comes from the heterogeneity across albums. We run the following regression:

$$p_{jrt} = \delta_{j} + \delta_{r} + \delta_{t} + \epsilon_{jrt}.$$

We find on Table 7 that the album part $\delta_j$ explains 75.3% of the total variance while the time effect $\delta_t$ has only a marginal impact, 1.9%. The variance explained by store effects $\delta_r$ is less than .04%, which confirms that the price policy is fixed at a national level.

<table><caption>Table 7: Analysis of variance</caption><thead><tr><th></th><th>prices</th><th>purchases</th></tr></thead><tbody><tr><th>Time effects</th><td>0.019</td><td>0.038</td></tr><tr><th>Album effects</th><td>0.753</td><td>0.103</td></tr><tr><th>Store effects</th><td>0.0004</td><td>0.019</td></tr></tbody></table>

$N = 245,630$ observations
The same decomposition of variance is done for purchases as well:

$$q_{jrt} = \delta_j + \delta_r + \delta_t + \epsilon_{jrt}.$$

It leads us to conclude that album, store and weekly effects explain a small though significant part of the variance in purchases. Product effects account for 10.3% of the heterogeneity in purchases only, stores explain 1.9% of the variance and time effects matter for 3.8%.

This analysis of variance enables us to conclude that heterogeneity matters in this framework and motivates the necessity of controlling for observed effects like time, album-store and price effects, which is done in the next section.

# 4 The firm

Contrary to consumers, firms do spend money and time to analyze consumers behavior in their marketing departments, to gather and record relevant data. For this reason it is much more likely that they behave optimally. We argue here that even though consumers may have naive expectations about the price process, the firm does not set prices naively. Its behavior turns out to be close to what an optimal firm would do.

First, from Figure 5 one can see that prices are sticky which contradicts the idea that the firm plays a static and repeated strategy. To check it formally, we regress current prices $p_t$ on past prices. Results are found in Table 8. We introduce one lag. Column I shows that the coefficient $\beta_{t-1}$ of $p_{t-1}$ is close to 1 and strongly significant as expected. Prices are serially correlated over time and not independent like in the prediction of Varian (1980). The rejection of $H_0: \beta_{t-1} = 0$ leads indeed to reject the static repeated game in our framework and to accept the idea that on the contrary, the firm behaves dynamically.

Second, adding more lags of the price as covariates, we find that the firm takes previous past prices into account when fixing prices, and not only the last one. Column II and III from Table 8 show that $p_t$ depends on $p_{t-2}, p_{t-3}, p_{t-4}, p_{t-5}$. We test $H_0: \beta_{t-2} = \beta_{t-3} = \beta_{t-4} = \beta_{t-5} = 0$. The F-stat is 582.3 and leads to a clear rejection of $H_0$ at the 5% level. Columns IV to VI do the same exercise with observations that do not come from imputation; they lead to the same conclusions. As a result, the firm does not fix prices according to the (first-) lagged price only.

Third, following the empirical analysis led by Pesendorfer (2002) on sales, we estimate the impact of the duration since the last price reduction on the probability of having a price reduction. We define $S_{jrt}$ as a covariate equal to 0 when the price is high and to 1
<table><caption>Table 8: Dynamics of prices</caption><thead><tr><th></th><th colspan="6">Price p<sub>t</sub></th></tr><tr><th></th><th>I</th><th>II</th><th>III</th><th>IV</th><th>V</th><th>VI</th></tr></thead><tbody><tr><th>p<sub>t-1</sub></th><td>0.889<sup>***</sup><br>(0.001)</td><td>0.931<sup>***</sup><br>(0.002)</td><td>0.926<sup>***</sup><br>(0.002)</td><td>0.887<sup>***</sup><br>(0.002)</td><td>0.907<sup>***</sup><br>(0.005)</td><td>0.867<sup>***</sup><br>(0.006)</td></tr><tr><th>p<sub>t-2</sub></th><td>.</td><td>0.001<br>(0.003)</td><td>0.001<br>(0.003)</td><td>.</td><td>0.018<sup>***</sup><br>(0.006)</td><td>0.032<sup>***</sup><br>(0.008)</td></tr><tr><th>p<sub>t-3</sub></th><td>.</td><td>-0.058<sup>***</sup><br>(0.002)</td><td>-0.007<sup>***</sup><br>(0.003)</td><td>.</td><td>-0.064<sup>***</sup><br>(0.004)</td><td>0.013<sup>***</sup><br>(0.008)</td></tr><tr><th>p<sub>t-4</sub></th><td>.</td><td>.</td><td>-0.030<sup>***</sup><br>(0.003)</td><td>.</td><td>.</td><td>-0.040<sup>***</sup><br>(0.007)</td></tr><tr><th>p<sub>t-5</sub></th><td>.</td><td>.</td><td>-0.026<sup>***</sup><br>(0.003)</td><td>.</td><td>.</td><td>-0.048<sup>***</sup><br>(0.005)</td></tr><tr><th>Album-store effects</th><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><th>Time effects</th><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><th>R<sup>2</sup></th><td>0.95</td><td>0.95</td><td>0.95</td><td>0.95</td><td>0.95</td><td>0.94</td></tr><tr><th>Number of observations</th><td>243,814</td><td>241,400</td><td>238,986</td><td>85,021</td><td>50,787</td><td>34,817</td></tr></tbody></table>

during the first period of a price reduction. We specify a simple Logit model:

$$S_{jrt} = 1[\gamma_a \text{ duration} + \delta t + \xi_{jr} + \epsilon_{jrt} > 0],$$

results of which are shown in Table 9. We reject $H_0: \gamma_a = 0$ against $H_a: \gamma_a > 0$ at the 5% level, which indicates that the probability of a price reduction is an increasing function of the duration since last price reduction. To check whether this relationship is stable, we allow $\gamma_a$ to vary over time (Column II): though the coefficient falls after 2004, the relationship is still increasing. Put differently, a price reduction is more likely to occur as time goes by.

In the same vein, we find that the length of a price reduction increases with the duration since the last price reduction, which is a best response of the firm to the accumulation of consumers. Indeed, while theoretically the peak of demand occurs during the first week of a price reduction, we have already observed that it takes several weeks to empty out the stock of consumers. As a result, the larger the interval between sales is, the more consumers cumulate and it takes longer to empty this stock out. We find evidence of such a correlation on Table 9.

To sum up, the firm fixes prices according to a rather complex and dynamic strategy. She does not play any repeated static game like in Varian (1980). Current prices depend not only on the past price but also on previous past prices. Moreover, the probability of a price reduction increases with the duration since the last promotion, which is consistent with a dynamic optimal behavior facing a cumulating demand. The firm takes the
<table><caption>Table 9: Fixation of price reductions</caption><thead><tr><th>Price reductions</th><th>Probability</th><th>Length</th></tr><tr><th>Model</th><th>Logit</th><th>OLS</th></tr></thead><tbody><tr><td>Duration since last sale</td><td>0.046<sup>***</sup><br>(0.001)</td><td>.</td></tr><tr><td>Duration since last sale×2003</td><td>.</td><td>0.069<sup>***</sup><br>(0.004)</td></tr><tr><td>Duration since last sale×2004</td><td>.</td><td>0.045<sup>***</sup><br>(0.002)</td></tr><tr><td>Duration since last sale×2005</td><td>.</td><td>0.045<sup>***</sup><br>(0.002)</td></tr><tr><td>Duration since last sale×2006</td><td>.</td><td>0.050<sup>***</sup><br>(0.002)</td></tr><tr><td>n</td><td>.</td><td>0.021<sup>**</sup><br>(0.009)</td></tr><tr><td>Album-store effects</td><td>Yes</td><td>Yes</td></tr><tr><td>Time trend</td><td>Yes</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>.</td><td>0.68</td></tr><tr><td>log L</td><td>-9,897</td><td>-9,870</td></tr><tr><td>Number of observations</td><td>88,192</td><td>88,192</td></tr></tbody></table>

past into account in her pricing strategy and behaves as if she were fully rational and intertemporal. However, this assumption should be properly tested with a structural model, comparing with what an optimal firm would do facing the actual demand. An other interesting exercise would consist in estimating a dynamic game between the firm and consumers assuming perfect foresight for all agents, compare profits, surplus and welfare with the actual ones.

# 5 Testing consumers' behavior

In this section, we provide empirical tests of agents rationality from our market-level data on prices and purchases, by documenting four empirical facts in relation with the four predictions of section 2. From Facts 1 and 2, we find evidence for Prediction 1 stating that dynamics matters. We reject Prediction 2 thanks to Fact 3 and the perfect foresight hypothesis, or at least the fact that consumers take their decisions based on a time dependent information set. Indeed, from a qualitative point of view, our data look like Figures 3 and 4, which means that consumers are either myopic or have a bounded rationality. Fact 4 helps us to reject Prediction 3 and the myopic behavior. We conclude that consumers use a time independent information set and form thus rather naive expectations: Fact 5 turns out to be consistent with Prediction 4.
## 5.1 Dynamics matters: consumers cumulate

**Fact 1** *During a price reduction, the pattern of purchases is decreasing.*

First, we document accumulation by showing evidence for peaks of demand at the beginning of price reductions. We define the covariate *during* as the elapsed time since the beginning of the price reduction: *during* is equal to 1 the first week of the price reduction, 2 the second week, etc. until the end of the price reduction. The covariate *during* is defined only when there is a price reduction. We perform then the simple regression to recover the (trend of the) pattern of purchases during price reductions, controlling for album-store and time effects:

$$q_{jrt} = \beta_d \text{ during} + \beta_x X_{jrt} + \xi_{jr} + \delta_t + \epsilon_{jrt}. \quad (7)$$

$X_{jrt}$ includes as controls the number of albums that are on sale in the store at time $t$, as well as the number of albums by the same author on sale, which both capture the intensity of the substitution effect. Note that the low price $p_{-jrt}$ could be introduced as a control variable: the usual simultaneity bias in demand equations would not arise here because this price might be correlated with $\xi_{jr}$ but not with the current idiosyncratic shock of demand $\epsilon_{jrt}$. Yet, because of the presence of $\xi_{jr}$, the identification of the price effect would be rather weak and rely on variations of this price within a given album-store only. Including the price as a covariate does not change our results.

<table><caption>Table 10: Demand during a sale</caption><thead><tr><th></th><th colspan="6">Purchases q<sub>jrt</sub></th></tr><tr><th></th><th>I</th><th>II</th><th>III</th><th>IV</th><th>V</th><th>VI</th></tr><tr><th></th><th>PR</th><th>PR</th><th>PR</th><th>S</th><th>S</th><th>S</th></tr></thead><tbody><tr><td>during</td><td>-0.262<sup>***</sup><br>(0.014)</td><td>-0.253<sup>***</sup><br>(0.014)</td><td>-0.272<sup>***</sup><br>(0.015)</td><td>-0.351<sup>***</sup><br>(0.022)</td><td>-0.355<sup>***</sup><br>(0.022)</td><td>-0.389<sup>***</sup><br>(0.024)</td></tr><tr><td>nb albums on sale</td><td>.</td><td>-0.125<sup>***</sup><br>(0.018)</td><td>.</td><td>.</td><td>-0.150<sup>**</sup><br>(0.024)</td><td>.</td></tr><tr><td>nb albums same author</td><td>.</td><td>1.238<sup>***</sup><br>(0.074)</td><td>1.149<sup>***</sup><br>(0.077)</td><td>.</td><td>1.841<sup>***</sup><br>(0.107)</td><td>1.687<sup>***</sup><br>(0.113)</td></tr><tr><td>Album-store effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Time effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Store-time effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>Album effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.59</td><td>0.60</td><td>0.56</td><td>0.60</td><td>0.60</td><td>0.56</td></tr><tr><td>Number of observations</td><td>28,382</td><td>28,382</td><td>28,382</td><td>16,727</td><td>16,727</td><td>16,727</td></tr></tbody></table>

We find on Table 10, Column II, that purchases are strongly decreasing during price reductions: $\beta_d = -0.253$ and is significant at usual levels. In Column III, we replace $\xi_{jr}$ (resp. $\delta_t$) by $\xi_{rt}$ (resp. $\delta_j$), in the case where time and album-store effects would not be
the appropriate fixed effects to control for. However, this specification does not explain as much variance (only 56%) as the previous one (60%) and yields close estimates for $\beta_d$. We control also for the number of albums on sale within the store: a negative sign (-0.125) accounts for a substitution effect between products, while we find a positive estimate (1.238) for the number of albums on sales by the same author, which accounts for bundle effects. Note that neither the introduction nor the removal (Column I) of such controls does change the result.

Focusing on sales only - as opposed to price reductions - does not change the results either, as shown by Columns IV to VI: the decrease turns out to be even higher with $\beta_d = -0.355$ (Column V).

Finally, discretizing *during*, we plot the average pattern of purchases during a price reduction (resp. a sale).

<figure><img src="image_8.png" /><figcaption>Figure 6: Evidence of accumulation</figcaption></figure>

Figure 6 shows that this pattern of demand is highly decreasing and falls continuously after the second week. Indeed, because of the aggregation of daily data, the first week of a price reduction is mixing days when the price was high and some days when it was low. As a result, purchases that week are logically on average lower than the week just after. However, this phenomenon does not occur afterwards and from the second week the decreasing pattern is clear. The magnitude of such an effect is large, which has to be related with Table 6 that pointed out a difference between -1.3 and -2.8 albums per week and per store without any control. From Figure 6 we learn that the effect is still higher by considering the second week rather than the first two weeks for the previous reason: for instance, there are 4 more albums sold in the second week than in
the tenth week of a price reduction. Furthermore, the small increase that can be noticed after the 11th week denotes some kind of return to a stationary level, consistently with the model exposed in Section 2. At the end, we notice that even after controlling for album-store and time effects, there is still an almost exponentially decreasing effect that one can interpret as the stock of consumers emptying out, which was already observed in descriptive statistics and that remains large and significant.

**Fact 2** The peak of demand at the beginning of price reductions is higher as *n* and $\bar{p}$ increase.

Second, we investigate how this peak varies as *n* and $\bar{p}$ increase, which is another way of testing whether Prediction 1 holds. From the pattern displayed by Figure 6, we define the peak as the average purchases during the first three weeks of the price reduction, at the exclusion of the first week. *n* refers to the duration of the period with a high price preceding the price reduction, $\bar{p}$ to the last high price charged and *p* is the current price during the price reduction.

<table><caption>Table 11: Peak at the beginning of price reductions</caption><thead><tr><th></th><th>Peak of demand</th></tr></thead><tbody><tr><td>p</td><td>-2.071***<br>(0.086)</td></tr><tr><td>p̄</td><td>2.069*<br>(1.347)</td></tr><tr><td>n</td><td>0.037***<br>(0.009)</td></tr><tr><td>Album-store effects</td><td>Yes</td></tr><tr><td>Time trend</td><td>Yes</td></tr><tr><td>Number of observations</td><td>2,833</td></tr><tr><td>R<sup>2</sup></td><td>0.73</td></tr></tbody></table>

Table 11 is consistent with Prediction 1 in the sense that the peak is higher as the duration since last sale increases, which claims again for a peak of accumulation. The impact of the high price $\bar{p}$ is positive though weakly significant. The magnitude of price effects is large, about -2 and +2, and the impacts of $\bar{p}$ and *p* tend to be very close to each other. One should not necessarily interpret this equality as evidence in favor of myopic consumers,<fnref n="1" /> as will be seen hereafter.

As a result, in our data, the existence of a peak of purchases coming from accumulation of consumers accounts for the importance of dynamics. We accept Prediction 1 and the idea that consumers cumulate.

<footnote n="1">¹since from Equation (3), these impacts should nearly coincide if accumulation matters or *n* is large</footnote>
## 5.2 Information is imperfect

**Fact 3** *The pattern of purchases is quite flat when the price stays constantly high before a price reduction.*

Third, we test for consumers' anticipation behavior and focus on periods with a high and constant price followed by a price reduction. As already argued, this restriction is motivated by the desire of having a test as pure as possible. Including periods with a constant but intermediate price, i.e. strictly between the highest and the lowest price level, would mix both phenomenons of anticipation and accumulation. At any intermediate price level, there is actually a decreasing pattern that has been put in evidence by Fact 1 and that has nothing to do with the anticipation behavior. Again, the price effect cannot be possibly identified on such periods.

To test our prediction, we define the covariate of interest *before* in such periods as the number of remaining weeks before the price reduction: reasoning backwards from the price reduction, *before* is equal to 1 the first week before a price reduction, 2 the week two weeks before, etc. until the beginning of the period with a high price. To test whether the pattern purchases is decreasing or flat in such periods, we propose to run the following regression:

$$q_{jrt} = \beta_b before + \beta_x X_{jrt} + \xi_{jr} + \delta_t + \epsilon_{jrt}. \quad (8)$$

<table><caption>Table 12: Demand before a sale</caption><thead><tr><th rowspan="2"></th><th colspan="6">Purchases q<sub>jrt</sub></th></tr><tr><th>I<br>PR</th><th>II<br>PR</th><th>III<br>PR</th><th>IV<br>S</th><th>V<br>S</th><th>VI<br>S</th></tr></thead><tbody><tr><td>before</td><td>-1.810<sup>-4</sup><br>(2.710<sup>-4</sup>)</td><td>-1.410<sup>-4</sup><br>(2.710<sup>-4</sup>)</td><td>-6.810<sup>-5</sup><br>(2.610<sup>-4</sup>)</td><td>0.0024***<br>(3.910<sup>-4</sup>)</td><td>0.0025***<br>(3.910<sup>-4</sup>)</td><td>0.0023***<br>(3.710<sup>-4</sup>)</td></tr><tr><td>nb albums on sale</td><td>.</td><td>-0.005***<br>(0.002)</td><td>.</td><td>.</td><td>-0.009***<br>(0.002)</td><td>.</td></tr><tr><td>nb albums same author</td><td>.</td><td>0.141***<br>(0.010)</td><td>0.145***<br>(0.011)</td><td>.</td><td>0.227***<br>(0.015)</td><td>0.231***<br>(0.016)</td></tr><tr><td>Album-store effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Time effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Store-time effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>Album effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.29</td><td>0.29</td><td>0.25</td><td>0.31</td><td>0.31</td><td>0.28</td></tr><tr><td>Number of observations</td><td>85,359</td><td>85,359</td><td>85,359</td><td>60,869</td><td>60,869</td><td>60,869</td></tr></tbody></table>

Here, the current price $\bar{p}_{jr}$ cannot be introduced as a covariate since its effect is not identified: the regression is performed during sequences of “high-then-low” prices for
which the price is always the highest observed at the album-store level. As a result, there is no variation in prices once $\xi_{jr}$ has been controlled for. A decreasing pattern of purchases in these periods must correspond to $\beta_b > 0$ since a higher value of *before* indicates that the price reduction is further away. On the contrary, $\beta_b = 0$ implies that the pattern is flat.

Table 12, Column II, presents the results: we see that $\beta_b = -1.4 \times 10^{-4}$ is not significant and we can't reject $H_0 : \beta_b = 0$ at the usual 5% level. In other words, there is no decreasing trend in the pattern of purchases when the price is high, and this pattern is quite flat. Contrary to the previous empirical evidence about Fact 1, the effect of *before* is not only insignificant but its magnitude, if any, is small. Restricting on sales only, and thus on more important price changes, yields a positive and significant estimate for $\beta_b$ (0.0025): this effect is however small in magnitude since it accounts for about 0.25% of sales per week.

<figure><img src="image_9.png" /><figcaption>Figure 7: Evidence of imperfect expectations - 1</figcaption></figure>

Again, we discretize *before* to get the whole pattern of purchases in periods with a high price. Results are displayed by Figure 7. The pattern of purchases during those periods is roughly flat. Similarly to what happened previously with the first week during a price reduction, the first week before a price reduction is mixing days with high and low prices: as a result, purchases are on average higher than the weeks before, which leads to a spurious higher level of purchases on this week. Excluding this week, the magnitude of the anticipation effect, if any, would be less than 0.1 in 20 weeks, i.e. 0.005 album per weeks.

Another way to test Prediction 2 is to define the covariate *after* as the elapsed duration since the last price reduction when the price is the highest: reasoning forwards from the
<table><caption>Table 13: Demand after a sale</caption><thead><tr><th></th><th colspan="6">Purchases q<sub>jrt</sub></th></tr><tr><th></th><th>I</th><th>II</th><th>III</th><th>IV</th><th>V</th><th>VI</th></tr><tr><th></th><th>PR</th><th>PR</th><th>PR</th><th>S</th><th>S</th><th>S</th></tr></thead><tbody><tr><td>after</td><td>-0.0009***<br>(2.610<sup>-4</sup>)</td><td>-0.0007***<br>(2.610<sup>-4</sup>)</td><td>-0.001***<br>(2.610<sup>-4</sup>)</td><td>-0.0013***<br>(3.810<sup>-4</sup>)</td><td>-0.001***<br>(3.810<sup>-4</sup>)</td><td>-0.0013***<br>(3.710<sup>-4</sup>)</td></tr><tr><td>nb albums on sale</td><td>.</td><td>-0.005***<br>(0.002)</td><td>.</td><td>.</td><td>-0.009***<br>(0.002)</td><td>.</td></tr><tr><td>nb albums same author</td><td>.</td><td>0.225***<br>(0.015)</td><td>0.143***<br>(0.011)</td><td>.</td><td>0.223**<br>(0.015)</td><td>0.225***<br>(0.016)</td></tr><tr><td>Album-store effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Time effects</td><td>Yes</td><td>Yes</td><td>No</td><td>Yes</td><td>Yes</td><td>No</td></tr><tr><td>Store-time effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>Album effects</td><td>No</td><td>No</td><td>Yes</td><td>No</td><td>No</td><td>Yes</td></tr><tr><td>R<sup>2</sup></td><td>0.29</td><td>0.29</td><td>0.25</td><td>0.31</td><td>0.31</td><td>0.28</td></tr><tr><td>Number of observations</td><td>85,359</td><td>85,359</td><td>85,359</td><td>60,869</td><td>60,869</td><td>60,869</td></tr></tbody></table>

beginning of a period with a high price, *after* is equal to 1 the first week of this period, 2 the week after, etc. until the last week of that period, immediately before a price reduction. We regress quantities on this covariate according to:

$$q_{jrt} = \beta_a a_{fter} + \beta_x X_{jrt} + \xi_{jr} + \delta_t + \epsilon_{jrt} \quad (9)$$

If consumers had perfect foresight or even rational expectations about the price process, $\beta_a < 0$ would indicate that the pattern is decreasing because of strategic delaying of purchases while $\beta_a = 0$ means that the pattern is flat. We find on Table 13, Column II, that the effect is significant at 5% but small: $\beta_a = -710^{-4}$.

Finally, analyzing both Tables 12 and 13 leads to the remark that substitution effects are still present and significant in periods with a high price.

However, on Figure 8 that exhibits the pattern of purchases after a price reduction, there is some kind of decreasing pattern. Yet the magnitude of such an effect is about -0.0125 units per week and per store, which accounts for 1% of quantities sold only. As a result, there is some asymmetry between what happens before and what happens after a price reduction. Moreover, consumers may be heterogeneous in the way they form their expectations: a small fraction of the population might have better expectations about the price process than others. Finally, this can also be due to the fact that stores do not change labels on albums after a price reduction.

One might worry whether these results are robust to the subdivision of albums according to their *n*. This is done in Appendix (Table 15) and yields roughly the same diagnosis.
<figure><img src="image_10.png" /><figcaption>Figure 8: Evidence of imperfect expectations - 2</figcaption></figure>

At the end, we believe that the effect pointed out by Figure 8 is still too weak to suggest that consumers use a time independent information set to make their decision. A small fraction of consumers would truly update their beliefs as time goes by, mainly remembering after a price reduction that they have better wait for the next one. Globally, we accept Prediction 2. Our data look thus qualitatively like Figure 3 or 4: they exhibit a flat pattern when prices are high, and a peak of demand at the beginning of a price reduction.

## 5.3 Dynamic decisions based on a time independent information set

**Fact 4** When the price is high, the demand decreases with the price gap, the gap between the current price and the price that is charged during a price reduction.

Fourth, to reject myopic behavior, we propose to show Fact 4 which indicates some strategic behavior. According to Prediction 3, a myopic demand should not be affected by anything but the current price, and especially be independent from the price gap $\bar{p}-\underline{p}$. This is in contrast to what happens when some information is used to form expectations, and when consumers wait more when they expect a higher price gap, which decreases the demand when the price is high. We perform the following regression:

$$q_{jrt} = \gamma \Delta p_{jrt} + \beta_x X_{jrt} + \xi_{jr} + \delta_t + \epsilon_{jrt} \quad (10)$$

Since *before* and *after* turned out to be not significant, we omit them from the regression; including them in the set of covariates does not alter the result.

In Table 14, we test and reject $H_0: \gamma = 0$ at the 5% level. We find that $\gamma = -0.016$; its negative sign indicates that there is some strategic delaying of purchases. When
the expected price gap is higher, more consumers wait and thus the current demand decreases. We notice that the substitution effects remain stable. As a result, consumers do take dynamic decisions of purchase and are neither completely informed nor completely uninformed about the future in this market. They hold rather wrong expectations about prices since correct expectations have already been rejected. To check whether this intermediate situation corresponds to the case described by Prediction 4, we document then the following.

**Fact 5** When the price is high, the demand decreases with the ratio between the price gap and the length of the interval between two price reductions.

We eventually perform the following regression:

$$q_{jrt} = \gamma_n \frac{\Delta p_{jrt}}{\bar{n}_{jr}} + \beta_x X_{jrt} + \xi_{jr} + \delta_t + \epsilon_{jrt} \quad (11)$$

<table><caption>Table 14: Demand when the price is high</caption><thead><tr><th></th><th colspan="2">Purchases q<sub>jrt</sub></th></tr></thead><tbody><tr><td>price gap</td><td>-0.016<sup>***</sup><br>(0.003)</td><td>.</td></tr><tr><td>price gap/n</td><td>.</td><td>-0.430<sup>***</sup><br>(0.091)</td></tr><tr><td>nb albums on sale</td><td>-0.004<sup>**</sup><br>(0.002)</td><td>-0.004<sup>**</sup><br>(0.002)</td></tr><tr><td>nb albums same author</td><td>-0.004<sup>**</sup><br>(0.002)</td><td>-0.004<sup>**</sup><br>(0.002)</td></tr><tr><td>Album-store effects ξ<sub>jr</sub></td><td>Yes</td><td>Yes</td></tr><tr><td>Time effects</td><td>Yes</td><td>Yes</td></tr><tr><td>Variance due to ξ<sub>jr</sub></td><td>0.80</td><td>0.80</td></tr><tr><td>Number of observations</td><td>85,359</td><td>85,359</td></tr></tbody></table>

To see why the information set that is used to form expectations over future prices does not vary over time, we consider the ratio between the price gap and the interval between two price reductions denoted $n$ in the model from Section 2. According to the time independent information hypothesis, the demand must decrease with this ratio that measures simply the gain from waiting until the next price reduction with respect to immediate purchase. Such a ratio encompasses the strategic effect when consumers have simple expectations of the form described by Equation 5: consumers expecting a higher price gap or a lower duration between price cuts should delay more their purchases, which decreases the current demand.

An empirical issue is to determine the relevant $n$. Put differently, we suspect the
interval between price reductions *n* to be endogenous. Note that this contrasts with *p* (and thus Δ*p*) which are very likely to be correlated to the album-store fixed effect ξ<sub>jr</sub> but not to the current shock of demand ϵ<sub>jrt</sub>. However, popular albums are likely to have a high *n* and episodic (shorter) sales with low prices, which is in line with what a rational firm would do to maximize profits. To overcome this issue, we decide to take for every album-store the mean of the intervals n<sub>jrt</sub> over all their observed relevant “high-then-low” sequences s *n*̄<sub>jr</sub> = <sup>1</sup>&frasl;<sub>S</sub> Σ<sub>s=1</sub><sup>S</sup> n<sub>jrt(s)</sub>. It is likely that *n*̄<sub>jr</sub> has reduced this endogeneity issue.

Results are displayed by Table 14 and show that $\gamma_n$ is about -0.43 and significant at
usual levels. We find thus evidence in favor of Fact 5.

Everything happens as if consumers had in mind an average length between price
reductions and formed simple expectations based on this static information, from which
they take dynamic decisions. Put in other words, dynamic actions seem to rely on time
independent information.

6 Discussion

6.1 Possible explanations

Indeed, behavioral economics suggests that consumer's rationality may be bounded because of limited capacity or limited memory: consumers may be far from *homo oeconomicus* and their behavior could actually look much simpler than a complex dynamic optimization. The validity of the full rationality hypothesis has often been challenged. Simon (1955) wished to replace *homo oeconomicus* with a man with bounded rationality and a whole part of the literature since Allais (1953) tries to check whether human behavior is conform to what is commonly assumed. Temptation and self-control (Gul and Pesendorfer (2001)), time inconsistency (Thaler and Shefrin (1981)) or hyperbolic discounting (Laibson (1997), O'Donoghue and Rabin (1999)) are evidence of non-fully rational behavior and have been widely documented through lotteries or experiments. Ellison (2006) already pointed out that bounded rationality matters in industrial organization.

On the one hand, the bounded rationality theory emphasizes that consumers may be
unable or unwilling to do all the computations required. It suggests that their ability to
optimize is limited. As documented by Vriend (1996), “agents capabilities are constrained
by perception, logical power and economic capacity”. This theory recognizes the role
played by heuristics and stresses the existence of psychological biases, of the *rule-of-thumb*
interfering with the rational decision process. This is the *limited capacity* explanation
proposed by Simon (1955) who suggested that consumers stopped their optimization at
the first *satisficing* solution reached. On the other hand, consumers may have a *limited*
*memory*: they do optimize but might do it on a restricted information set, reaching therefore a second-best solution. This imperfect monitoring of the state of the world is likely to happen because human beings considered as physical objects are intrinsically limited in the amount of information they can receive. Another explanation for the limited memory hypothesis is that information is costly to gather – and thus valuable. The role of information was emphasized first by Stigler (1961) who inspires models with search costs. Consumers facing such costs decide to acquire information only when it is profitable for them to do so. As a result, consumers may decide not to collect further information, which bounds their memory *de facto*. In the model of Reis (2006) for instance, consumers are *inattentive* in the sense that in multi-periods games they decide not to pay attention to prices every period. Finally, consumers may also forget the past.

Moreover, heterogeneity among consumers’ degree of rationality matters. Some consumers may have no information on past prices, which prevents them from forming correct expectations: this may be the case of occasional shoppers; or they have access to information as regular shoppers do, but they are not able to manage such an information set and restrict their analysis to a smaller set. Some theoretical papers had introduced naive and sophisticated consumers. Varian (1980) invokes heterogeneous search costs to distinguish among informed and uninformed consumers who have a limited information set. This idea was also considered by Pesendorfer (2002) who distinguishes loyal consumers from shoppers. Sobel (1984) considers that some part of the population cannot delay strategically their purchase because of limited capacity. These forms of imperfect rationality are however not able to fully rationalize the results obtained in this paper.

## 6.2 Implications

In this market, consumers behave as if they were expecting a Markov process for prices. Indeed, the scenario that corresponds the most to consumers’ behavior is the one where consumers expect a price reduction with a constant probability over time, that is $E(p_{t+1}|p_t = \bar{p}) = (1 - \lambda)p_t + \lambda \bar{p}$. This Markov assumption is often made in the literature devoted to the structural estimation of dynamic discrete-choice models (DDCM) like Hendel and Nevo (2006) and Gowrisankaran and Rysman (2011). It is somehow considered as an approximation of a true consumer’s behavior having perfect foresight. Yet it entails a significant reduction of the computational burden. We showed that such an assumption can be tested, and how we accepted this hypothesis in our market.

Making the assumption of once-for-all expectations *versus* perfect foresight or rational expectations may impact the demand function, the computation of the firm’s optimal policy and thus on welfare. A step in this direction that is left for further research would be to estimate a structural model of demand relying on this assumption and compare
results obtained under myopia or perfect foresight.

## 6.3 Limits

First, these results are specific to the music industry and concern only a segment of consumers who are loyal to the chain considered. They may sound not too much surprising since the catalogue and thus the information set are large, and remembering past prices for all albums would be rather demanding in this context.

<figure><img src="image_11.png" /><figcaption>Figure 9: Heterogeneity of average durations between price reductions</figcaption></figure>

In this vein, there is no clear seasonality in the timing of such promotions: every week, about 7.5% of albums have a sale. There is no clear increase of sales immediately before, during or after Christmas. As a result, anticipating sales is not an easy task. Each album has its own price cycle: the average interval between two promotions is distributed according to Figure 9. Even though there is a mode at about 28 weeks, there is a whole distribution of these durations. This complicates predictions of future price falls that consumers can make: consumers simply cannot remember all price cycles for the whole set of albums. Nevertheless, since the probability of a price reduction always increases with the elapsed duration since the last price reduction as will be shown next, consumers holding rational expectations should take it into account and some decreasing pattern should be observed.
Third, in other industries like clothing, where sales have a fixed and public schedule (at the beginning of January and June in France), it would actually be interesting to perform the same test. Consumers would be almost all informed and may only differ in their ability (or willingness) to optimize, which would enable to disentangle the limited memory from the limited capacity effect. Similarly, consumers are more likely to be optimizers and to form correct beliefs for housing or for cars where more substantial amounts of money are involved. Chevalier and Goolsbee (2009) for instance have a similar test in nature but distinct in practice for college textbooks: they accept the idea that students are forward-looking, which can be explained by the fact that students are rather optimizers.

Fourth, competition is absent from the current analysis. However, it is hard to imagine that the flat pattern is caused by the fact that consumers go systematically more to the competitor(s) at the beginning than at the end of a period with high prices.

Finally, one could imagine other explanations for the flat pattern. For instance, cohorts of consumers could be heterogeneous. In case when they are more numerous before price reductions, there could be a decreasing pattern coming from time dependent expectations exactly compensated by an increasing pattern due to the size of cohorts. However, this should hold for every price reduction, given that these price reductions are specific to some album-store and do not all occur at the same time.

# 7 Conclusion

To conclude, this paper has tested usual assumptions about agents expectations and dynamic behavior using market-level data. Strategic consumers with perfect foresight or revising correctly their beliefs would delay more and more their purchase as the price reduction approaches; consumers with once-for-all expectations would not behave like this, which generates a declining pattern of purchases when the price is constantly high in the former case, and a constant pattern in the latter, which should be observed in the data. On our data, we test and accept the hypothesis of once-for-all expectations. Similarly, the firm may fix prices in a more or less dynamic fashion, and here her behavior is close to what an optimal firm would do.

These results are coherent with rational consumers expecting a simple though wrong Markov price process. Though this may not be surprising in this setting, we believe that such a test could easily be performed before the estimation of structural DDCM models since it reinsures about the validity of assumptions regarding agents rationality. Moreover, if these results do not affect the estimation of dynamic models of demand that already rely on a Markov assumption for the price process, they do impact the firm's equilibrium price strategy and the welfare analysis as well.
A natural extension would consist in measuring the loss caused by this lack of anticipation: facing the same price process, how would consumers with correct beliefs behave? Another interesting question would be to compute the equilibrium of the game in which both the firm and consumers are fully rational, and compare it with the observed one.
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A List of albums

<table><thead><tr><th>AUTHOR</th><th>TITLE</th><th>SALES</th><th>AUTHOR</th><th>TITLE</th><th>SALES</th></tr></thead><tbody><tr><td>YOUNG</td><td>harvest</td><td>17727</td><td>SUPERTRAMP</td><td>verybestofvol1</td><td>2712</td></tr><tr><td>QUEEN</td><td>platinumcollection</td><td>15457</td><td>RAGEAGAINSTTHEMACHINE</td><td>bombtrack</td><td>2661</td></tr><tr><td>CHAPMAN</td><td>tracychapman</td><td>14271</td><td>RIVERS</td><td>johneehooker</td><td>2564</td></tr><tr><td>DIDO</td><td>noangel</td><td>14264</td><td>SCORPIONS</td><td>bestof</td><td>2451</td></tr><tr><td>DOORS</td><td>doors</td><td>11174</td><td>PATRICE</td><td>ancientspirit</td><td>2426</td></tr><tr><td>NIRVANA</td><td>nevermind</td><td>9989</td><td>SUPERTRAMP</td><td>breakfastinamerica</td><td>2417</td></tr><tr><td>LEDZEPPELIN</td><td>ledzeppeliniv</td><td>9831</td><td>MARILYNMANSON</td><td>antichristsuperstar</td><td>2390</td></tr><tr><td>VELVETUNDERGROUND</td><td>andywarhol</td><td>9686</td><td>SLIPKNOT</td><td>slipknot</td><td>2382</td></tr><tr><td>THECLASH</td><td>londoncalling</td><td>9671</td><td>POLICE</td><td>reggattadeblanc</td><td>2366</td></tr><tr><td>HARPER</td><td>welcometothecruelworl</td><td>9565</td><td>MARILYNMANSON</td><td>hollywood</td><td>2354</td></tr><tr><td>SYSTEMOFADOWN</td><td>toxicity</td><td>9155</td><td>SIMPLYRED</td><td>greatesthits</td><td>2335</td></tr><tr><td>COLDPLAY</td><td>parachutes</td><td>9150</td><td>U2</td><td>joshuatree</td><td>2311</td></tr><tr><td>PINKFLOYD</td><td>darksideofthemoon</td><td>9116</td><td>U2</td><td>war</td><td>2294</td></tr><tr><td>BEATLES</td><td>one</td><td>8610</td><td>OASIS</td><td>morningglorywhatsthe</td><td>2293</td></tr><tr><td>DOORS</td><td>lawoman</td><td>8601</td><td>DEPECHEMODE</td><td>101live</td><td>2186</td></tr><tr><td>LEDZEPPELIN</td><td>ledzeppelini</td><td>8082</td><td>RAMMSTEIN</td><td>liveausberlin</td><td>2006</td></tr><tr><td>CASAL</td><td>luzcasal</td><td>7175</td><td>MARILYNMANSON</td><td>mechanicalanimals</td><td>1975</td></tr><tr><td>NIRVANA</td><td>unpluggedinnewyork</td><td>7014</td><td>TOURNEEUROPEENNE1</td><td>live</td><td>1970</td></tr><tr><td>PINKFLOYD</td><td>wall</td><td>6913</td><td>VAYACONDIOS</td><td>bestof</td><td>1944</td></tr><tr><td>LEDZEPPELIN</td><td>ledzeppelini</td><td>6913</td><td>WYATT</td><td>rockbottom</td><td>1940</td></tr><tr><td>BUCKLEY</td><td>livealoympia1995</td><td>6846</td><td>COHEN</td><td>greatesthits</td><td>1829</td></tr><tr><td>SEXPISTOLS</td><td>nevermindthebollocks</td><td>6801</td><td>MARILYNMANSON</td><td>smellslikechildren</td><td>1826</td></tr><tr><td>JOPLIN</td><td>greatesthits</td><td>6747</td><td>QUEEN</td><td>anightattheopera</td><td>1768</td></tr><tr><td>MADONNA</td><td>immaculatecollection</td><td>6712</td><td>POP</td><td>lustforlife</td><td>1761</td></tr><tr><td>PINKFLOYD</td><td>wall</td><td>6550</td><td>SINATRA</td><td>mywaythebestoffrank</td><td>1748</td></tr><tr><td>ABBA</td><td>abbagold</td><td>6393</td><td>BLUESBROTHERS</td><td>verybestof</td><td>1722</td></tr><tr><td>EAGLES</td><td>hotelcalifornia</td><td>6286</td><td>IRONMAIDEN</td><td>numberofthebeast</td><td>1720</td></tr><tr><td>LEDZEPPELIN</td><td>ledzeppelini</td><td>5971</td><td>LEDZEPPELIN</td><td>remastersvoll</td><td>1687</td></tr><tr><td>HARPER</td><td>fightforyourmind</td><td>5557</td><td>METALLICA</td><td>sanfranciscosymphonyor</td><td>1683</td></tr><tr><td>CONTE</td><td>bestof</td><td>5485</td><td>JOPLIN</td><td>pearl</td><td>1679</td></tr><tr><td>PINKFLOYD</td><td>wishyouwerehere</td><td>5324</td><td>CROSBYSTILLSANDNASH</td><td>dejavu</td><td>1659</td></tr><tr><td>LOVE</td><td>foreverchanges</td><td>5248</td><td>DOORS</td><td>bestof</td><td>1586</td></tr><tr><td>COLLINS</td><td>hits</td><td>5205</td><td>PINKFLOYD</td><td>more</td><td>1565</td></tr><tr><td>REDHOTCHILIPEPPERS</td><td>californication</td><td>5202</td><td>SMITH</td><td>easter</td><td>1552</td></tr><tr><td>PINKFLOYD</td><td>atomheartmother</td><td>5201</td><td>REED</td><td>berlin</td><td>1495</td></tr><tr><td>BOBDYLAN</td><td>essentialbobdylan</td><td>4945</td><td>ZZTOP</td><td>greatesthits</td><td>1413</td></tr><tr><td>SYSTEMOFADOWN</td><td>systemofadown</td><td>4909</td><td>KSCHOICE</td><td>paradiseinme</td><td>1408</td></tr><tr><td>BEATLES</td><td>bleu19671970</td><td>4508</td><td>BEATLES</td><td>rubbersoul</td><td>1362</td></tr><tr><td>DOORS</td><td>waitingforthesun</td><td>4402</td><td>WAITS</td><td>mulevariations</td><td>1298</td></tr><tr><td>WHO</td><td>whosnextremasterise7</td><td>4346</td><td>HENDRIX</td><td>axisboldaslove</td><td>1291</td></tr><tr><td>SMITHS</td><td>queenisdead</td><td>4189</td><td>SIMPLEMINDS</td><td>liveinthecityoflight</td><td>1276</td></tr><tr><td>DEEPPURPLE</td><td>madeinjapan</td><td>4091</td><td>MADONNA</td><td>ultimatecollection</td><td>1269</td></tr><tr><td>BEATLES</td><td>sergentpepperslonelyh</td><td>3988</td><td>POGUES</td><td>verybestof</td><td>1260</td></tr><tr><td>BEATLES</td><td>whitealbum2cd</td><td>3912</td><td>SANTANA</td><td>abraxas</td><td>1216</td></tr><tr><td>MADONNA</td><td>music</td><td>3904</td><td>WHO</td><td>liveatleeds</td><td>1210</td></tr><tr><td>BEATLES</td><td>rouge19621966</td><td>3736</td><td>QUEEN</td><td>newsoftheworld</td><td>1164</td></tr><tr><td>RAMMSTEIN</td><td>mutter</td><td>3676</td><td>SOMERVILLE</td><td>greatesthits</td><td>1092</td></tr><tr><td>CLAPTON</td><td>unplugged</td><td>3570</td><td>MAMASANDTHEPAPAS</td><td>verybestof</td><td>1042</td></tr><tr><td>BEATLES</td><td>abbeyroad</td><td>3499</td><td>BEATLES</td><td>help</td><td>1033</td></tr><tr><td>HENDRIX</td><td>electricladyland</td><td>3468</td><td>MARILYNMANSON</td><td>lasttour</td><td>1019</td></tr><tr><td>PINKFLOYD</td><td>meddle</td><td>3367</td><td>QUEEN</td><td>innuendo</td><td>997</td></tr><tr><td>HENDRIX</td><td>experiencehendrix</td><td>3319</td><td>NOMI</td><td>20plusbelleschansons</td><td>980</td></tr><tr><td>DIRESTRAITS</td><td>brothersinarms</td><td>3233</td><td>MARILYNMANSON</td><td>portraitofanamericanf</td><td>905</td></tr><tr><td>PINKFLOYD</td><td>animals</td><td>3167</td><td>QUEEN</td><td>livemagic</td><td>816</td></tr><tr><td>REDHOTCHILIPEPPERS</td><td>bloodsugarsexmagik</td><td>3154</td><td>KNOPFLER</td><td>sailingtophiladelphia</td><td>772</td></tr><tr><td>HARPER</td><td>willtolive</td><td>3144</td><td>TYLER</td><td>bestof</td><td>758</td></tr><tr><td>STEVENS</td><td>teaforthetillerman</td><td>3132</td><td>ZAPPA</td><td>hotrats</td><td>685</td></tr><tr><td>ROLLINGSTONES</td><td>flashpoint</td><td>3054</td><td>BUCKLEY</td><td>sketches</td><td>639</td></tr><tr><td>RAMAZZOTTI</td><td>eros</td><td>3021</td><td>CARPENTERS</td><td>gold</td><td>588</td></tr><tr><td>MADNESS</td><td>onestepbeyond</td><td>2839</td><td>KNOPFLER</td><td>neckandneck</td><td>504</td></tr><tr><td>JETHROTULL</td><td>aqualung</td><td>2742</td><td></td><td></td><td></td></tr></tbody></table>
# B Imputation of prices and smoothing

We describe here the issue of recovering prices when they are not observed because there is no purchase.

– Step 0: From daily to weekly

We aggregate daily to weekly observations through the procedure followed by Pe-
sendorfer (2002) using data from the Chicago Booth GSB. Basically, the weekly price
will correspond to the “most frequent” price of the week, “most frequent” being weighted
by the amount of purchases. We restrict our attention to the subsample of albums that
are sold at least once during the two first and last months in every big French store; the
price of such albums should exceed 2 euros. We are left with 1207 albums-stores during
203 weeks i.e. 245,021 observations.

- Step 1: Defining regular prices

For every album-store we define a set of regular prices based on observed prices as the
subset of prices that were charged at least three – non necessarily consecutive – weeks
during the whole period. An album-store can have between 1 and 15 of such prices.

- Step 2: Imputing regular prices

We impute the closest higher regular price to any observed price, provided that the
difference is larger than the maximum of 20 cents or 2% of the price, when we impute
the closest lower regular price.

- Step 3: Imputing missing prices

Then we impute missing prices (a “zero”) using these regular prices.

– Step 3a: When there is either a one-week (20,628 observations) or a two-week zero (17,636 observations), we impute the maximum adjacent price.

– Step 3b: For longer periods of zeroes (73,205 observations), we impute the most frequent price at the nationwide level for this album when it is available and when it belongs to the set of regular prices defined at the album-store level.

– Step 3c: In the other cases (5,230 observations), we impute the maximum adja-
cent price.

- Step 4: Smoothing

We smooth these price patterns by first eliminating one-week price changes and then
second-week price changes. We thus replace observed or imputed prices by the closest
adjacent price in such cases.
<table><caption>Table 15: Demand when the price is high</caption><thead><tr><th></th><th colspan="9">Purchases q<sub>jrt</sub></th></tr><tr><th></th><th>3 &le; n &le; 7</th><th>8 &le; n &le; 13</th><th>14 &le; n &le; 19</th><th>20 &le; n &le; 25</th><th>26 &le; n &le; 31</th><th>32 &le; n &le; 37</th><th>38 &le; n &le; 43</th><th>44 &le; n &le; 49</th></tr></thead><tbody><tr><th>before</th><td>-0.058<br>(0.040)</td><td>-0.006<br>(0.012)</td><td>0.027***<br>(0.004)</td><td>0.013***<br>(0.004)</td><td>-0.013***<br>(0.003)</td><td>-0.007**<br>(0.003)</td><td>0.010***<br>(0.003)</td><td>0.006*<br>(0.003)</td></tr><tr><th>after</th><td>0.071*<br>(0.039)</td><td>0.002<br>(0.012)</td><td>-0.030***<br>(0.004)</td><td>-0.012***<br>(0.004)</td><td>0.013***<br>(0.004)</td><td>0.006**<br>(0.003)</td><td>-0.010***<br>(0.003)</td><td>-0.006*<br>(0.003)</td></tr><tr><th>Album-store effects</th><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><th>Time effects</th><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td><td>Yes</td></tr><tr><th>Number of observations</th><td>1,485</td><td>4,380</td><td>9,800</td><td>7,999</td><td>5,654</td><td>9,463</td><td>8,108</td><td>5,521</td></tr></tbody></table>
<table>
  <tr>
    <td>G 9001</td>
    <td>J. FAYOLLE et M. FLEURBAEY<br/>Accumulation, profitabilité et endettement des entreprises</td>
    <td></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</td>
    <td>I. STAPIC<br/>Les échanges internationaux de services de la France dans le cadre des négociations multilatérales du GATT<br/>Juin 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</td>
    <td>P. SEVESTRE<br/>L'économétrie 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</td>
    <td>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</td>
    <td>N. GREENAN et D. GUELLEC<br/>Coordination within the firm and endogenous growth</td>
  </tr>
  <tr>
    <td>G 9101</td>
    <td>Equipe AMADEUS<br/>Le modèle AMADEUS - Première partie - Présentation générale</td>
    <td>G 9207</td>
    <td>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</td>
    <td>B. CREPON, E. DUGUET, D. ENCAOUA et P. MOHNEN<br/>Cooperative, non cooperative R &amp; 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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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</td>
    <td>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-économique</td>
    <td>G 9400</td>
    <td>L. BLOCH, J. COLIN-SEDILLOT<br/>Les théories sur la structure optimal 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</td>
    <td>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</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 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>Equipes Amadeus (INSEE), Banque de France, Métric (DP)<br/>Présentation des propriétés des principaux modèles macroéconomiques du Service Public</td>
  </tr>
  <tr>
    <td>G 9314</td>
    <td>B. CREPON - E. DUGUET<br/>Research &amp; 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 ?<br/>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/>Théorie 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/>Persistence 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 Economie 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 - Erasme - 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-BENSAÏD<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 Etudes<br>et Synthèses Economiques - 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>paraitre</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 Etudes et<br>Synthèses Economiques - 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>Evolution 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>Evaluation 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>Evolution 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>Evolution 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>Equivalent 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 de la 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-t-elle aussi aux non-diplômés ?

G2001/03 I. BRAUN-LEMAIRE
Evolution 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
Evaluation 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

- Retroposition 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 Familiale 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 : interprétation 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 Techologies, 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 microéconométrique

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. DOURGNON - 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 DESTINE

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, recentrage 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
Microsimuler 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 croisssance potentielle à long terme

G2009/10 D. BLANCHET - J. LE CACHEUX - V. MARCUS
Adjusted net savings and other approaches to sustainability: some theroretical 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
Projeter 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 tertiarisation 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 et 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 macroéconométrique 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