<table><caption>Table 7: Regressions of Log IT Intensity of Capital On Measures of Firm Scale</caption><thead><tr><th rowspan="2"></th><th colspan="4">IT Intensity of Labor</th><th colspan="4">IT Intensity of Capital</th><th colspan="2">IT Intensity of Cost</th></tr><tr><th>Workers</th><th>Workers</th><th>Wage Bill</th><th>Wage Bill</th><th>Total</th><th>Total</th><th>Tangible</th><th>Tangible</th><th>Cost</th><th>Cost</th></tr></thead><tbody><tr><td colspan="11"><strong>Panel 1: Software (Stock)</strong></td></tr><tr><td>Number of plants</td><td>0.0015<br>(0.0002)</td><td>0.0014<br>(0.0002)</td><td></td><td></td><td>0.0014<br>(0.0002)</td><td>0.0016<br>(0.0002)</td><td></td><td></td><td>0.0013<br>(0.0002)</td><td></td></tr><tr><td>Number of occupational layers</td><td></td><td>0.2623<br>(0.0047)</td><td>0.2230<br>(0.0047)</td><td></td><td></td><td>0.2558<br>(0.0049)</td><td>0.2603<br>(0.0050)</td><td></td><td>0.2250<br>(0.0047)</td><td></td></tr><tr><td>Observations</td><td>562,858</td><td>562,858</td><td>562,997</td><td>562,997</td><td>518,716</td><td>518,716</td><td>517,470</td><td>517,470</td><td>563,027</td><td>563,027</td></tr><tr><td>R2</td><td>0.2214</td><td>0.2255</td><td>0.2143</td><td>0.2173</td><td>0.2237</td><td>0.2276</td><td>0.2238</td><td>0.2278</td><td>0.2186</td><td>0.2217</td></tr><tr><td>Number of destination countries</td><td>0.0276<br>(0.0004)</td><td>0.0243<br>(0.0004)</td><td></td><td></td><td>0.0225<br>(0.0004)</td><td>0.0232<br>(0.0004)</td><td></td><td></td><td>0.0238<br>(0.0004)</td><td></td></tr><tr><td>Number of products</td><td></td><td>0.0065<br>(0.0002)</td><td>0.0059<br>(0.0002)</td><td></td><td></td><td>0.0054<br>(0.0002)</td><td>0.0056<br>(0.0002)</td><td></td><td>0.0057<br>(0.0002)</td><td></td></tr><tr><td>Observations</td><td>278,803</td><td>278,803</td><td>279,590</td><td>279,590</td><td>261,609</td><td>261,609</td><td>261,144</td><td>261,144</td><td>279,902</td><td>279,902</td></tr><tr><td>R2</td><td>0.1958</td><td>0.1871</td><td>0.1887</td><td>0.1817</td><td>0.1867</td><td>0.1806</td><td>0.1875</td><td>0.1811</td><td>0.1921</td><td>0.1854</td></tr><tr><td colspan="11"><strong>Panel 2: Hardware (Stock)</strong></td></tr><tr><td>Number of plants</td><td>0.0040<br>(0.0001)</td><td>0.0040<br>(0.0001)</td><td></td><td></td><td>0.0036<br>(0.0001)</td><td>0.0040<br>(0.0001)</td><td></td><td></td><td>0.0039<br>(0.0001)</td><td></td></tr><tr><td>Number of occupational layers</td><td></td><td>0.0986<br>(0.0009)</td><td>0.0700<br>(0.0009)</td><td></td><td></td><td>0.1124<br>(0.0010)</td><td>0.1251<br>(0.0010)</td><td></td><td>0.0735<br>(0.0009)</td><td></td></tr><tr><td>Observations</td><td>2,696,655</td><td>2,696,655</td><td>2,698,300</td><td>2,698,300</td><td>2,622,236</td><td>2,622,236</td><td>2,622,998</td><td>2,622,998</td><td>2,698,872</td><td>2,698,872</td></tr><tr><td>R2</td><td>0.3913</td><td>0.3933</td><td>0.3632</td><td>0.3640</td><td>0.4003</td><td>0.4027</td><td>0.4319</td><td>0.4347</td><td>0.3275</td><td>0.3286</td></tr><tr><td>Number of destination countries</td><td>0.0337<br>(0.0002)</td><td>0.0299<br>(0.0002)</td><td></td><td></td><td>0.0258<br>(0.0002)</td><td>0.0272<br>(0.0002)</td><td></td><td></td><td>0.0291<br>(0.0002)</td><td></td></tr><tr><td>Number of products</td><td></td><td>0.0084<br>(0.0001)</td><td>0.0078<br>(0.0001)</td><td></td><td></td><td>0.0068<br>(0.0001)</td><td>0.0071<br>(0.0001)</td><td></td><td>0.0076<br>(0.0001)</td><td></td></tr><tr><td>Observations</td><td>553,427</td><td>553,427</td><td>555,879</td><td>555,879</td><td>546,058</td><td>546,058</td><td>546,478</td><td>546,478</td><td>555,847</td><td>555,847</td></tr><tr><td>R2</td><td>0.2831</td><td>0.2628</td><td>0.2533</td><td>0.2366</td><td>0.3129</td><td>0.3033</td><td>0.3339</td><td>0.3237</td><td>0.2226</td><td>0.2058</td></tr></tbody></table>

Note: In all panels the dependent variable is the logarithm of IT stock intensity. Standard errors are reported in brackets. In columns (1)-(4) we report results of IT intensity of labor, in columns (5)-(8) we report results for IT intensity of capital, and in columns (9) and (10) we report results of IT intensity of cost. The time period is 1995-2007. In panel 1 the sample is all firms sampled by EAE, and in panel 2 the sample is BRN firms. All columns include a full set of 3-digit industry classification fixed effects interacted with year fixed effects and a full set of cohorts fixed effect (pre 1980, 1980-1993, 1993-1995 ... 2005-2007) and normalised age fixed effects. A semi-elasticity of 0.0276 of software stock per worker to the number of destination countries means that exporting to one new country raises software stock per worker by 2.76%.

10%).

A number of potential issues may complicate the interpretation of our results. First, we may be concerned that small firms face some fixed cost of adopting IT, may not perfectly report their IT investment, or may face different costs of IT compared to large firms in our data. Second, we may be concerned that small firms covered in our data are not representative of all small firms in the French economy. To address these concerns, we show that the relationship between firm size and IT intensity also appears among large firms in our data. Figure 2 already shows that the positive relationship between size and IT intensity is fairly consistent across different brackets of size, particularly in the case of software where the issues of selection and measurement error are less pronounced.<fnref n="86" /> To address this issue more

<footnote n="86">⁸⁶As we already mentioned, the hardware data includes office furniture investments, which biases our measure of hardware intensity upward particularly for middle-size firms for which office capital may constitute the largest share of their capital stock. See footnote 24 for a discussion of how this issue appears in Figure 2. With regard to selection, note that the source of our hardware data, includes firms that have voluntarily chosen to file in the BRN tax regime below certain revenue thresholds. It is likely that small firms selecting to file in the BRN regime expect higher future growth, which may also be correlated with currently higher IT intensities. This would make small firms in the BRN</footnote>
<table><caption>Table 8: Regressions of IT Intensity of Cost on Log Firm Size, by Bins of Employment</caption><thead><tr><th></th><th colspan="10">IT Intensity of Cost</th></tr><tr><th></th><th>[1;50]</th><th>[50;100]</th><th>[100;250]</th><th>[250;1000]</th><th>≥ 1000</th><th>[1;50]</th><th>[50;100]</th><th>[100;250]</th><th>[250;1000]</th><th>≥ 1000</th></tr></thead><tbody><tr><td colspan="11"><strong>Panel 1: Software (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.2871<br>(0.0057)</td><td>0.2528<br>(0.0136)</td><td>0.2199<br>(0.0140)</td><td>0.2861<br>(0.0185)</td><td>0.2761<br>(0.0370)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td></td><td></td><td></td><td></td><td>0.2159<br>(0.0065)</td><td>0.2202<br>(0.0167)</td><td>0.1959<br>(0.0170)</td><td>0.2906<br>(0.0213)</td><td>0.3024<br>(0.0395)</td></tr><tr><td>Observations</td><td>379,543</td><td>91,406</td><td>66,022</td><td>30,925</td><td>6,375</td><td>379,603</td><td>91,430</td><td>66,030</td><td>30,933</td><td>6,375</td></tr><tr><td>R2</td><td>0.2506</td><td>0.2132</td><td>0.2216</td><td>0.2716</td><td>0.3715</td><td>0.2478</td><td>0.2117</td><td>0.2202</td><td>0.2705</td><td>0.3718</td></tr><tr><td colspan="11"><strong>Panel 2: Hardware (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.0812<br>(0.0009)</td><td>0.7282<br>(0.0061)</td><td>0.5073<br>(0.0058)</td><td>0.2934<br>(0.0070)</td><td>0.1400<br>(0.0127)</td><td></td><td></td><td></td><td></td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td></td><td></td><td></td><td></td><td>-0.0343<br>(0.0010)</td><td>0.5140<br>(0.0074)</td><td>0.3700<br>(0.0070)</td><td>0.2135<br>(0.0082)</td><td>0.0911<br>(0.0132)</td></tr><tr><td>Observations</td><td>2,563,488</td><td>132,537</td><td>93,307</td><td>41,372</td><td>8,295</td><td>2,563,741</td><td>132,577</td><td>93,338</td><td>41,393</td><td>8,295</td></tr><tr><td>R2</td><td>0.3752</td><td>0.3428</td><td>0.3847</td><td>0.3817</td><td>0.4572</td><td>0.3735</td><td>0.2960</td><td>0.3525</td><td>0.3647</td><td>0.4514</td></tr></tbody></table>

Note: In both panels the dependent variable is the logarithm of IT stock intensity of cost. Standard errors are reported in brackets. In columns (1)-(5) and (6)-(10) we report results of regressions for firms in various bins of total number of employees: less than 50 employees, 50 to 100, ... up to more than 1000 employees. The independent variable is the logarithm of firm size either proxied by sales or value added. The time period is 1995-2007. In panel 1 the sample is all firms sampled by EAE, and in panel 2, the sample is BRN firms. All columns include a full set of 3-digit industry classification fixed effects interacted with year fixed effects and a full set of cohorts fixed effect (pre 1980, 1980-1993, 1993-1995 ... 2005-2007) and normalised age fixed effects. An elasticity of 0.2871 means that raising sales by a factor of 2 raises the IT intensity of cost by 28.71%.

directly, Table 8 replicates the results of Table 6 on the IT intensity of cost for samples of firms in different brackets of employment size. The results for the IT intensity of software clearly demonstrates that the relationship between size and IT intensity is fairly robust across different brackets of firm size, with the coefficients between 0.2 and 0.3. Again, the results show more variability in the case of hardware data, but the coefficients are still nonmonotonic, first increasing and then decreasing.

<footnote>sample unsuitable representatives for the sample of all small French firms. In contrast, the source of our software data, the EAE dataset, contains a representative sample for firms with fewer than 20 employees.</footnote>
<table><caption>Table 9: Regressions of IT Intensity on Log Firm Size (Within Firm)</caption><thead><tr><th rowspan="2"></th><th colspan="4">IT Intensity of Labor</th><th colspan="3">IT Intensity of Capital</th><th colspan="2">IT Intensity of Cost</th></tr><tr><th>Workers</th><th>Workers</th><th>Wage Bill</th><th>Wage Bill</th><th>Total</th><th>Total</th><th>Tangible</th><th>Tangible</th><th>Costs</th><th>Costs</th></tr></thead><tbody><tr><td colspan="11"><strong>Panel 1: Software (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.2042<br>(0.0326)</td><td>0.1455<br>(0.0327)</td><td></td><td></td><td>0.3422<br>(0.0337)</td><td>0.3533<br>(0.0338)</td><td></td><td>0.1702<br>(0.0326)</td><td></td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>0.2161<br>(0.0288)</td><td>0.1432<br>(0.0288)</td><td></td><td>0.3296<br>(0.0297)</td><td>0.3379<br>(0.0298)</td><td></td><td>0.1621<br>(0.0287)</td><td></td><td></td></tr><tr><td>Observations</td><td>233,654</td><td>233,376</td><td>233,507</td><td>233,189</td><td>221,456</td><td>221,319</td><td>221,676</td><td>221,614</td><td>233,548</td><td>233,230</td></tr><tr><td>R2</td><td>0.8361</td><td>0.8325</td><td>0.8319</td><td>0.8281</td><td>0.8313</td><td>0.8270</td><td>0.8311</td><td>0.8272</td><td>0.8327</td><td>0.8288</td></tr><tr><td colspan="11"><strong>Panel 2: Hardware (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.2612<br>(0.0097)</td><td>0.1686<br>(0.0097)</td><td></td><td></td><td>0.3706<br>(0.0101)</td><td>0.3765<br>(0.0102)</td><td></td><td>0.1874<br>(0.0095)</td><td></td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>0.1470<br>(0.0081)</td><td>0.0437<br>(0.0082)</td><td></td><td>0.2482<br>(0.0084)</td><td>0.2533<br>(0.0085)</td><td></td><td>0.0660<br>(0.0080)</td><td></td><td></td></tr><tr><td>Observations</td><td>248,038</td><td>249,026</td><td>248,995</td><td>250,111</td><td>244,282</td><td>245,286</td><td>243,095</td><td>244,175</td><td>248,466</td><td>249,591</td></tr><tr><td>R2</td><td>0.8689</td><td>0.8691</td><td>0.8467</td><td>0.8466</td><td>0.9078</td><td>0.9077</td><td>0.9177</td><td>0.9175</td><td>0.8485</td><td>0.8493</td></tr></tbody></table>

Note: The dependent variable is the logarithm of IT stock intensity. Standard errors are reported in brackets. In columns (1)-(4) we report results of IT intensity of labor, in columns (5)-(8) we report results for IT intensity of capital, and in columns (9) and (10) we report results of IT intensity of cost. The independent variable is the logarithm of firm size either proxied by sales or value added. The time period is 1995-2007. In panel 1 the sample is all firms sampled by EAE, and in panel 2, the sample is BRN firms. All columns include a full set of firm fixed effects, and 3-digit industry classification fixed effects interacted with year fixed effects. An elasticity of 0.2042 of software stock per worker to sales means that raising sales by a factor of 2 raises software stock per worker by 20.42%.

## B.2 Within-Firm

Table 9 reports the results of the following regression:

$$ IT \ Intensity_{it} = \eta Size_{it} + FE_{kt} + FE_{i} + v_{it}, \quad (44) $$

where $FE_i$ is a firm fixed effect and $FE_{kt}$ stands for the industry-time fixed effects. The specification allows us to examine the within-firm relationship between firm size and IT intensity. The table shows that the results of the previous section are *not* driven by a potential confounding cross-sectional relationship between IT-biased productivity and size.

The within-firm estimates in Table 9 still leave us with the possibility that the residual $v_{it}$ in Equation (44) could be correlated with size. To identify the contribution of nonhomotheticity to the correlation between size and IT intensity, we rely on demand shocks to different export destinations of firms as an exogenous source of variation in their expected potential for growth. To the extent that firms take advantage of these opportunities to expand their activities, we should find a first stage effect of the instrument on firm sales and value added. The idea behind this strategy has been used in a number of recent papers (e.g., Hummels et al., 2014; Mayer et al., 2015; Aghion et al., 2017; Garin and Silveiro, 2017; Panon, 2019). As we will see below, our specifications identify the within-firm relationship between size and IT intensity. As a result, our key identification assumption is that the *variations in value of the demand shock measures above are uncorrelated with firm-level residual v<sub>it</sub>'s in Equation (44).*
**Export Demand Shock Instruments** We construct the product-destination-level export demand shocks for firm *i* at time *t* as

$$ds_{it}^{p} = \sum_{np} \Lambda_{inp,0} (im \overline{p}_{np,t}^{FR} - im \overline{p}_{p,t}^{FR}), \quad (45)$$

where $\Lambda_{inp}$ denotes destination-$n$/product-$p$ share of firm-$i$ exports, $im \overline{p}_{np,t}^{FR}$, the destination-$n$/product-$p$ log import from all countries except France, and $im \overline{p}_{p,t}^{FR}$ the product-level average value of the log import across all other destinations. With this specification, we avoid including the component of demand in any given product-destination that might be driven by potential productivity shocks to all French exporters.

**Data for Export Demand Shocks** To construct the instruments, we use the French customs data that provides the value of the exports of firms by destination and product (at the nc8 level) spanning the 1995-2007 period. The data allows us to compute the share of each destination-$n$/product-$p$ share of firm-$i$ exports ($\Lambda_{inp}$ in Equation (45)) as the corresponding average for years 1995 and 1996. To build the product-level demand shocks in Equation (45), we rely on the COMTRADE bilateral Trade Flows Data, and in particular on the harmonized version of the data provided in the BACI dataset. This dataset includes the values of flows from each exporter to each importing destination as HS6 code product-level.<fnref n="87" /> We use this information to compute for each product in each destination country the sum of all imports from all other countries, leaving out France. We construct the instrument $ds_{it}^p$ for years 1997-2007.

**Empirical Specification** For the results of this section, we limit our attention to the sample of exporting firms. Table 5 of the online appendix compares the summary statistics of this sample with the sample of all firms. As is well-known, exporting firms are typically larger than other firms. The table shows that they are, in addition, also slightly more IT intensive than average firms (Fort et al., 2017).

Table 10 present the results of applying the following specification in the sample of exporting firms

$$IT \ Intensity_{it} - \overline{IT \ Intensity}_{i} = \eta(\text{Size}_{it} - \overline{\text{Size}}_{i}) + FE_{kt} + v_{it}, \quad (46)$$

where $IT \ Intensity_{it}$ denotes a measure of the relative demand for IT inputs for a firm $i$ in an industry $k$ at time $t$, $FE_{kt}$ stands for a flexible set of industry-time fixed effects (at the 3-digit level), $y_{it}$ is the sales or value added of the firm (depending on the specification), and $\overline{y}_i$ is the firm-level mean of log firm size $y_{it}$. We estimate Equation (46) with 2SLS, using the shocks defined in Equations (45) as instruments for $y_{it} - \overline{y}_i$. Results in Tables 10 (and 11) are provided with product demand shocks from 1997 to 2007.

The coefficients are positive and significant for the majority of specifications. They are also close in magnitude to, even if larger than, those reported in Table 9 for the within-firm effects. Note that the sample of firms in Table 10 is much smaller, only featuring relatively large exporting firms for which we can construct the instrument. Moreover, Table 11 presents the same estimates, when weighted by each firm's initial share of exports in total sales to avoid relying on firms for which exports constitutes a very small share of sales (see e.g. Aghion et al., 2017). The weighted results are typically smaller in both magnitude of the estimates and the standard errors.<fnref n="88" />

<footnote n="87">⁸⁷We use the concordance procedure made available by Van Beveren et al. (2012) to map CN8 products code over time, and to more aggregated HS6 product codes.</footnote>

<footnote n="88">⁸⁸Note that the only negative coefficients in Table 11, for the hardware intensity of costs, change sign and are positive in Table 10.</footnote>
<table><caption>Table 10: Reduced Form Identification of the Elasticity of IT Intensity on Log Firm Size</caption><thead><tr><th rowspan="2"></th><th colspan="4">IT Intensity of Labor</th><th colspan="4">IT Intensity of Capital</th><th colspan="2">IT Intensity of Cost</th></tr><tr><th>Workers</th><th>Workers</th><th>Wage Bill</th><th>Wage Bill</th><th>Total</th><th>Total</th><th>Tangible</th><th>Tangible</th><th>Costs</th><th>Costs</th></tr></thead><tbody><tr><td colspan="11"><strong>Panel 1: Software (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>1.3035<br>(0.2586)</td><td>0.7505<br>(0.2519)</td><td></td><td></td><td>1.0834<br>(0.2533)</td><td>0.9512<br>(0.2581)</td><td></td><td></td><td>1.0362<br>(0.2522)</td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>1.5605<br>(0.3362)</td><td>0.8848<br>(0.3322)</td><td></td><td></td><td>1.1500<br>(0.3275)</td><td>1.2513<br>(0.3359)</td><td></td><td>1.2316<br>(0.3289)</td><td></td></tr><tr><td>Observations</td><td>104,640</td><td>103,570</td><td>104,988</td><td>103,844</td><td>100,130</td><td>99,011</td><td>100,322</td><td>99,215</td><td>105,120</td><td>103,982</td></tr><tr><td colspan="11"><strong>Panel 2: Hardware (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>1.5525<br>(0.0834)</td><td>1.0627<br>(0.0775)</td><td></td><td></td><td>1.1301<br>(0.0756)</td><td>1.1174<br>(0.0749)</td><td></td><td></td><td>0.1637<br>(0.0696)</td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>1.9002<br>(0.1196)</td><td>1.3000<br>(0.1046)</td><td></td><td></td><td>1.4004<br>(0.1019)</td><td>1.3815<br>(0.1008)</td><td></td><td>0.1901<br>(0.0872)</td><td></td></tr><tr><td>Observations</td><td>99,096</td><td>98,119</td><td>99,821</td><td>98,905</td><td>99,744</td><td>98,873</td><td>99,715</td><td>98,795</td><td>99,772</td><td>98,876</td></tr></tbody></table>

Note: The dependent variable is the demeaned logarithm of IT stock intensity. Standard errors are reported in brackets. In columns (1)-(4) we report results of IT intensity of labor, in columns (5)-(8) we report results for IT intensity of capital, and in columns (9) and (10) we report results of IT intensity of cost. The independent variable is the logarithm of firm size either proxied by sales or value added, instrumented by product demand shocks. The time period is 1997-2007. In panel 1 the sample is all exporting firms sampled by EAE, and in panel 3, the sample is exporting BRN firms. All columns include a full set of 3-digit industry classification fixed effects interacted with year fixed effects. An elasticity of 1.3035 of software stock per worker to sales means that raising sales by a factor of 2 raises software stock per worker by 130.35%.

<table><caption>Table 11: Reduced Form Identification of the Elasticity of IT Intensity on Log Firm Size (Weighted)</caption><thead><tr><th rowspan="2"></th><th colspan="4">IT Intensity of Labor</th><th colspan="4">IT Intensity of Capital</th><th colspan="2">IT Intensity of Cost</th></tr><tr><th>Workers</th><th>Workers</th><th>Wage Bill</th><th>Wage Bill</th><th>Total</th><th>Total</th><th>Tangible</th><th>Tangible</th><th>Costs</th><th>Costs</th></tr></thead><tbody><tr><td colspan="11"><strong>Panel 1: Software (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.5656<br>(0.2615)</td><td>0.3196<br>(0.2514)</td><td></td><td></td><td>0.4419<br>(0.2632)</td><td>0.5192<br>(0.2523)</td><td></td><td></td><td>0.5422<br>(0.2499)</td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>0.8018<br>(0.3666)</td><td>0.4519<br>(0.3617)</td><td></td><td></td><td>0.7278<br>(0.3784)</td><td>0.8511<br>(0.3556)</td><td></td><td>0.6926<br>(0.3510)</td><td></td></tr><tr><td>Observations</td><td>102,481</td><td>101,439</td><td>102,803</td><td>101,685</td><td>98,146</td><td>97,067</td><td>98,336</td><td>97,264</td><td>102,939</td><td>101,826</td></tr><tr><td colspan="11"><strong>Panel 2: Hardware (Stock)</strong></td></tr><tr><td>Size (proxied by sales)</td><td>0.6962<br>(0.0874)</td><td>0.3597<br>(0.0842)</td><td></td><td></td><td>0.5328<br>(0.0848)</td><td>0.4892<br>(0.0827)</td><td></td><td></td><td>-0.0341<br>(0.0793)</td><td></td></tr><tr><td>Size (proxied by VA)</td><td></td><td>0.9066<br>(0.1430)</td><td>0.4598<br>(0.1287)</td><td></td><td></td><td>0.7853<br>(0.1246)</td><td>0.6865<br>(0.1162)</td><td></td><td>-0.0474<br>(0.1266)</td><td></td></tr><tr><td>Observations</td><td>96,370</td><td>95,434</td><td>97,066</td><td>96,194</td><td>97,036</td><td>96,218</td><td>97,006</td><td>96,136</td><td>97,021</td><td>96,171</td></tr></tbody></table>

Note: The dependent variable is the demeaned logarithm of IT stock intensity. Standard errors are reported in brackets. In columns (1)-(4) we report results of IT intensity of labor, in columns (5)-(8) we report results for IT intensity of capital, and in columns (9) and (10) we report results of IT intensity of cost. The independent variable is the logarithm of firm size either proxied by sales or value added, instrumented by product demand shocks. The time period is 1997-2007. In panel 1 the sample is all exporting firms sampled by EAE, and in panel 3, the sample is exporting BRN firms. All columns include a full set of 3-digit industry classification fixed effects interacted with year fixed effects. An elasticity of 0.5656 of software stock per worker to sales means that raising sales by a factor of 2 raises software stock per worker by 56.56%. Estimation is weighted by the share of export in total sales in 1995-1996.
# C Additional Theoretical Results

## C.1 Firm-Level Production Function and Organizational Complexity

Following Lucas (1978), we distinguish between technology and organization as two distinct aspects of firm productivity. The technology of production is simply the idea (or, blueprint) describing how to transform inputs to the desired output. However, even if firms pursue the same technology, they may still differ in the organizational efficiency with which they implement it. Accordingly, we assume that a firm is characterized by an organizational input O as well as its technological efficiency A. The output Y of the firm is given by

$$Y = [A \mathcal{X}(O, X_N)]^{\frac{1}{\gamma}}, \quad (47)$$

where the parameter $1/\gamma$ controls the degree of returns to scale, and where $\mathcal{X}(\cdot, \cdot)$ is a CES aggregator of the bundle of non-IT inputs $X_N$ and the organizational input O:

$$\mathcal{X}(O, X_N) = \left( O^{\frac{\sigma-1}{\sigma}} + X_N^{\frac{\sigma-1}{\sigma}} \right)^{\frac{\sigma}{\sigma-1}}. \quad (48)$$

The key assumption is that, while the technology is an exogenous constant $A \equiv e^{\theta}$, the organizational input of the firm endogenously varies according to:

$$O = X_I \times Y^{-\epsilon} \times e^{\phi}. \quad (49)$$

Equation (49) assumes that organizational input O depends on an intrinsic firm-level organizational efficiency $e^{\phi}$. In addition, it also allows for diminishing returns to the organizational input as the output Y rises, due to potential increase in organizational complexity. Finally, it allows for the firm to raise its organizational input by adjusting its level of IT inputs $X_I$.

Combining Equations (47)-(49), we arrive at our specification of nhCES production functions provided in Equation (9). The construction above provides a specific interpretation of the nonhomotheticity of IT demand in Equation (10): larger firms optimally choose higher IT intensities in response to the fall in their organizational efficiency due to higher complexities of production.

**Discussion** Equation (47) assumes that *organization* is a firm-specific factor that may potentially generate decreasing returns. This assumption is by no means novel. In his Principles of Economics, Marshall identifies organization as a fourth factor of production, in addition to labor, capital, and land. Coase (1937) argues that “decreasing returns to the entrepreneur function” is a key factor in determining the boundary of the firm. To justify firm-level decreasing returns, McKenzie (1959) defines a firm-specific *entrepreneurial input*, Lucas (1978) refers to it as the *managerial talent* of the firm’s manager, and Atkeson and Kehoe (2005) interpret it as the *organizational capital* of the firm. Our concept of organizational input is also in line with the concept of the firm-level *economic competencies* that is considered to be a core component of the intangible capital of firms (Haskel and Westlake, 2018).

At least since Williamson (1967), many economic theories have provided micro-foundations for such firm-level organizational limits to scale.<fnref n="89" /> These models offer various mechanisms through which the complexities of coordi-

<footnote n="89">⁸⁹Some approaches emphasize the agency issues inherent in delegation and the formation of hierarchies (see Mukherjee, 2012, for a review), while others focus on the complexities of solving allocative decisions within the firm (see Garicano and Van Zandt, 2012). In particular, in theories of knowledge hierarchies the complexity of the process</footnote>
nation and communication, both within the firm and also between the firm and its buyers and suppliers, may rise as the firm scale grows. Equation (49) offers a stylized account of such organizational limits to scale, inspired by the span-of-control model of Lucas (1978) (nested in our model for the case of $\sigma = 1$).<fnref n="90" /> The latter focuses solely on the limits to the ability of a manager to supervise production over increasing scales of inputs. In contrast, Equation (49) accounts for the organizational limits to the scale in terms of firm output $Y$. A larger scale of output $Y$ brings about complexities that stem from organizing production tasks over larger scales of inputs and outputs. On the input side, the firm potentially has to find and coordinate with more intermediate suppliers, hire more or different types of workers, procure more machines, and manage across a large set of inputs. On the output side, it has to potentially manage larger inventories, coordinate with more buyers or across more markets, provide support services to a larger set of customers, organize larger scale marketing efforts, and solve larger delivery or distribution problems.

Equation (49) further generalizes the benchmark span-of-control model by allowing firms to endogenously deploy IT in order to enhance their organizational efficiency. A sizable body of empirical work has documented the connection between IT and the organizational efficiency of the firm. Brynjolfsson and Hitt (2000) discuss numerous case studies that showcase the effect of IT on the organizational practices of businesses. A variety of firm-level cross sectional studies have documented the complementarity between IT adoption and organizational capital (e.g., Bresnahan et al., 2002; Brynjolfsson and Hitt, 2003; Baker and Hubbard, 2004). In particular, Bartel et al. (2007) use detailed firm-level data on setup times, run times, and inspection times to show how IT improves the efficiency of organizing multiple production processes within the firm. As another example, Bloom et al. (2014) find that the adoption of IT impacts the organization of the firm in terms of span of control over individual workers. In sum, IT allows firms to more effectively apply their technology or core competencies to a larger scale of inputs, across a wider range of activities, and to serve more buyers and markets.

## C.2 Nonhomothetic Demand and Returns to Scale

In this section we examine the properties of general production functions that are compatible with nonhomothetic IT demand in Equation (6). The following lemma establishes two properties for the elasticities of substitution and scale of the production functions that give rise to nonhomothetic IT demand with a constant elasticity with respect to output.

**Lemma 4.** Consider a continuous, differentiable, and monotonically increasing production function $Y = F(X_N, X_I)$ such that the set $\{(X_N, X_I) \ge 0 | Y \le F(X_N, X_I)\}$ is strictly convex for all $Y$. Assume that the corresponding cost minimization problem yields factor demand functions satisfying Equation (6). Then, along any expansion path in the $(X_N, X_I)$-space<fnref n="91" /> the production function satisfies the following two properties:<fnref n="92" />

1. The elasticity of substitution between IT and non-IT inputs is constant everywhere.

2. The production function is “not” homogeneous of a constant degree, that is, there is “no” $\epsilon > 0$ such that for all $Z > 0$ and all $(X_N, X_I)$ the production function satisfies $F(ZX_N, ZX_I) = Z^\epsilon F(X_N, X_I)$.

of dealing with production errors changes endogenously with the scale of operation (Garicano, 2000; Garicano and Rossi-Hansberg, 2006; Caliendo and Rossi-Hansberg, 2012). Another alternative follows the approach of Simon (1962) and examines the implications of bounded rationality and the limits to information processing (e.g., Van Zandt and Radner, 2001).

<footnote n="90">⁹⁰Appendix C.3 provides a derivation of the Lucas span-of-control model in the special case of $\sigma = 1$, i.e., the case where the elasticity of substitution between technology and organization is unity.</footnote>

<footnote n="91">⁹¹An expansion path is a curve with constant marginal rate of transformation $F_I/F_N \equiv (\partial F/\partial X_I)/(\partial F/\partial X_N)$.</footnote>

<footnote n="92">⁹²See proof in Section 1.4 of the online appendix.</footnote>
We can alternatively state the result of Lemma 4 in terms of the properties of the cost function, when we fix relative factor input prices $W_I/W_N$. The first part of the lemma tells us that the elasticity of substitution $\partial \log(X_I/X_N)/\partial \log(W_I/W_N)$ only depends on relative input prices $W_I/W_N$, and not output $Y$. In other words, if we consider in the space of inputs $(X_N, X_I)$ paths characterized by a constant marginal rate of substitution, the normal vectors to this curve form parallel vectors everywhere along the curve.

More importantly, the second part says that the cost elasticity, which is the reciprocal of the scale elasticity, varies with the scale of the firm output $Y$. In other words, if the IT factor input has a higher output elasticity than the non-IT factor input, their scale elasticity is bound to change when firms change their scale of operation. Specifically, the lemma rules out a constant-returns-to-scale (CRS) production function.

We may naturally wonder whether the scale elasticity rises or falls with output. The next lemma shows that to answer this question we need to impose further structure on the production function. More specifically, the answer to this question hinges on whether the two inputs are gross complements or gross substitutes.

**Proposition 1.** Consider a production function $\mathcal{F}$ satisfying the conditions in Lemma 4. Assume, in addition, that the scale elasticity is constant in the limit that either input goes to zero, that is, there is some $\epsilon_k > 0$ such that for all $Z > 0$ we have

$$ \lim_{X_k \to 0} \frac{\mathcal{F}(Z X_N, Z X_I)}{\mathcal{F}(X_N, X_I)} = Z^{\epsilon_k}, \quad k \in \{N, I\}. $$

Then, if the elasticity of substitution is less (greater) than 1 and non-increasing (nondecreasing) in the marginal rate of transformation $\mathcal{F}_I/\mathcal{F}_N$, the scale elasticity is monotonically decreasing (increasing) in output $Y$ along a curve with constant marginal rate of transformation.<fnref n="93" />

Lemma 1 shows that, under fairly mild conditions on the production function, the relationship between scale elasticity and firm size is monotonic and depends on the elasticity of substitution between IT and non-IT inputs. In particular, when the elasticity of substitution is constant, with an elasticity of substitution below 1, larger firms have higher scale elasticities. The opposite is the case with an elasticity of substitution greater than 1. To better illustrate this result, below we will consider two extreme examples: the first being a production function with a zero elasticity of substitution between the two inputs and the second being the polar case with perfect substitutability. We will see that, as the firm size grows, the scale elasticity falls and rises in the first and second examples, respectively.

**Example 1.** Consider a nonhomothetic Leontief production function $Y = \mathcal{F}(X_N, X_I)$ defined implicitly through

$$ Y = \min\{X_N, Y^{-\eta} X_I\}, \quad \eta > 0. $$

In any cost minimizing solution, we have $Y = X_N = X_I^{1/(1+\eta)}$, which implies $X_I/X_N = Y^\eta$ satisfying condition (6). Given factor prices $(W_N, W_I)$, the corresponding cost function is given by $C(Y; W_N, W_I) = W_N Y + W_I Y^{1+\eta}$. Therefore, the cost elasticity, which is the reciprocal of the scale elasticity, satisfies

$$ \frac{\partial \log C}{\partial \log Y} = 1 + \eta \Omega_I(W_N, W_I; Y), $$

where we have defined $\Omega_I(W_N, W_I; Y) \equiv W_I Y^\eta / (W_N + W_I Y^\eta)$ as the cost share of IT-inputs. This share is monotonically increasing in the level of output $Y$, implying that the cost elasticity is increasing in output.

<footnote n="93">⁹³See proof in Section 1.4 of the online appendix.</footnote>
**Example 2.** Consider a linear production function $Y = F(X_N, X_I)$ defined as

$$Y = X_N + Y^{\eta} X_I, \quad 0 < \eta < 1.$$

Although strictly speaking, this production function does not satisfy condition (6), its factor demand and cost functions demonstrate quasi-nonhomothetic behavior. In particular, when the scale of output is small enough to satisfy $W_I/W_N \ge Y^{\eta}$, we have $X_N = Y$ and $X_I = 0$. On the other hand, when the scale of output is large enough such that $W_I/W_N < Y^{\eta}$, we have $X_N = 0$ and $X_I = Y^{1-\eta}$. The corresponding cost function is

$$C(W_N, W_I; Y) = \begin{cases} W_N Y, & W_I/W_N \ge Y^{\eta}, \\ W_I Y^{1-\eta}, & W_I/W_N \le Y^{\eta}. \end{cases}$$

In stark contrast to Example 1, in this case the cost elasticity falls as output rises. With $W_I/W_N \ge Y^{\eta}$, the production function has constant returns to scale whereas for $W_I/W_N < Y^{\eta}$, the scale elasticity is $1/(1-\eta)$ strictly greater than 1.

The intuition for the result above is as follows. As output rises, Equation (6) implies that IT inputs grow faster than non-IT inputs because of their higher elasticity with respect to output. The rise in IT inputs raises the marginal product of non-IT inputs, which means that we have to further raise the non-IT input in order to again equalize the marginal product to the non-IT factor price. When the elasticity of substitution is below 1, the required rise in the non-IT input is sufficiently large to make the cost function increasingly convex as the output rises. The situation is reversed when the elasticity of substitution is greater than 1.

### C.3 Connection to the Lucas’ Span-of-Control Model

Lucas (1978) assumed that managerial productivity is heterogeneous across firms, and the equilibrium size of firms is determined through span-of-control limits. Specifically, he assumed that $X_N = f(K, L)$ is a constant-returns-to-scale aggregator of capital and labor, and the output is given by $Y = B g(X_N)$ where $g(\cdot)$ is a concave function and $B$ is the managerial productivity of the firm. Comparing this specification with our construction in Section C.1, consider the case of $\gamma = 1$, Cobb-Douglas functional forms $f(K, L) = K^{\alpha}L^{1-\alpha}$, and $g(X_N) = X_N^{1-\psi}$.

Next, we provide a mapping between the specification above for the Lucas model and our construction in Section C.1. Without loss of generality, we generalize Equation (48) to $\mathcal{X} = (\xi^{\frac{1}{\sigma}} X_N^{1-\frac{1}{\sigma}} + (1-\xi)^{\frac{1}{\sigma}} O^{1-\frac{1}{\sigma}})^{\frac{\sigma}{\sigma-1}}$ with coefficients $\xi \in (0, 1)$. Substituting the expression for $O$ in this equation, we find

$$\mathcal{X} = \left( \xi^{\frac{1}{\sigma}} (X_N)^{\frac{\sigma-1}{\sigma}} + (1-\xi)^{\frac{1}{\sigma}} \left( e^{\phi} X_I Y^{-\epsilon} \right)^{\frac{\sigma-1}{\sigma}} \right)^{\frac{\sigma}{\sigma-1}}. \quad (50)$$

Now, let us apply the l'Hopital's rule, to find the limit of the expression as $\sigma \to 1$:

$$\lim_{\sigma \to 1} \log \frac{\mathcal{X}}{X_N} = \theta + (1-\xi) \left( \phi + \log \left( \frac{X_I}{X_N} \right) - \epsilon \log Y \right) + \omega,$$

where $\omega$ is a constant.
Substituting the expression above in Equation (47) with $\gamma = 1$, we find:

$$Y = e^{\omega + \frac{\theta+(1-\xi)\phi}{1+(1-\xi)\kappa}} \times X_I^{\frac{1-\xi}{1+(1-\xi)\kappa}} \times X_N^{\frac{\xi}{1+(1-\xi)\kappa}}.$$

Comparing this equation with the Lucas specification $Y = B X_N^{1-\psi}$, we find that the two coincide if we set

$$\psi \equiv \frac{(1-\xi)(1+\epsilon)}{1+(1-\xi)\epsilon},$$

$$B \equiv e^{\omega + \frac{\theta+(1-\xi)\phi}{1+(1-\xi)\kappa}} \times X_I^{\frac{1-\xi}{1+(1-\xi)\kappa}}.$$

This expression is in line with the Lucas model, assuming that we take the input $X_I$ of each firm to be an exogenous value.

## C.4 A Fixed-Cost Model of IT

Consider the following fixed-cost-of-IT production function $Y = ZF_{f\epsilon}(X_N, X_I)$ defined as

$$Y = \begin{cases} ZX_N, & X_I = 0, \\ \Delta_I Z \left(\frac{X_I}{\xi}\right)^{\xi} \left(\frac{X_N-\psi_I}{1-\xi}\right)^{1-\xi}, & X_I > 0, \end{cases}$$

where $\psi_I$ and $\Delta_I$ are constants that captures the fixed cost of adopting IT (in units of non-IT inputs) and its corresponding productivity premium, respectively. In order for IT to be adopted by some firms, assume that $\Delta_I > W^\xi$, where W is the relative price of non-IT inputs. We can then show that the cost function is given by

$$C(Y) = \begin{cases} \frac{Y}{Z}, & Y \le Y^*, \\ \psi_I + \frac{W^\xi Y}{\Delta_I Z}, & Y \ge Y^*, \end{cases}$$

where $Y^* = Z\psi_I/(1-W^\xi/\Delta_I)$, denotes the threshold of firm size above which firms adopt nonzero IT inputs. Accordingly, the share of IT in total costs is given by

$$\Psi = \frac{W X_I}{C(Y)} = \begin{cases} 0, & Y \le Y^*, \\ \frac{\xi}{1+\psi_I \frac{\Delta_I Z}{W^\xi Y}}, & Y \ge Y^*, \end{cases}$$

which increases from 0 to $\xi > 0$ as the size Y goes from zero to infinity.

We can characterize the output elasticity of relative demand and the elasticity of substitution between IT and non-IT inputs as follows. First, we calculate the elasticity of relative demand with respect to output:

$$\frac{\partial \log(X_I/X_N)}{\partial \log Y} = \frac{\partial \log \left( \frac{\xi/W}{1-\xi + \psi_I \frac{\Delta_I Z}{W^\xi Y}} \right)}{\partial \log Y} = \frac{1}{1+(1-\xi) \frac{W^\xi Y}{\psi_I \Delta_I Z}} > 0.$$

This shows that the IT intensity is increasing in firm size both on the extensive and the intensive margins. However, this elasticity converges to zero as Y goes to infinity. Next, we derive the elasticity of substitution between IT and
non-IT inputs

$$-\frac{\partial \log(X_I/X_N)}{\partial \log W} = -\frac{\partial \log}{\partial \log W} \left( \frac{\xi/W}{1-\xi + \psi_I \frac{\Delta_I}{W^\xi} \frac{Z}{Y}} \right) = 1 - \frac{1}{1+(1-\xi) \frac{W^\xi Y}{\psi_I \Delta_I \frac{Z}{Y}}}$$

which we find to be less than unity.

Finally, let us examine the returns to scale properties of the production function. First, the production function features increasing returns to scale for $Y \ge Y^*$. Second, the scale elasticity is decreasing in size for $Y \ge Y^*$, as its reciprocal the cost elasticity is given by

$$\mathcal{E}(Y) = \frac{\partial \log \mathcal{C}(Y)}{\partial \log Y} = \frac{1}{1 + \psi_I \frac{\Delta_I}{W^\xi} \frac{Z}{Y}},$$

and increases from $W^\xi/\Delta_I$ to 1 as $Y$ goes from $Y^*$ to infinity.

## C.5 Aggregate Elasticity of Substitution

To characterize the two components of Equation (30), the following lemma first presents the comparative statics of the IT cost share and output with respect to the relative IT price.

**Lemma 5.** The response of IT share and the output of firms with productivity state $\vartheta$ are given by

$$\frac{d\tilde{\Omega}(\vartheta)}{dw} = (1-\sigma)\tilde{\Omega}(\vartheta)(1-\tilde{\Omega}(\vartheta)) \frac{\left[1+\zeta\epsilon\left(\frac{dp}{dw}+\frac{dy}{\lambda dw}\right)\right](1+\frac{\epsilon}{\gamma}\tilde{\Omega}(\vartheta))}{1+\frac{\epsilon}{\gamma}\tilde{\Omega}(\vartheta)\left[1+\zeta(\gamma+\eta(1-\tilde{\Omega}(\vartheta)))\right]}, \quad (51)$$

$$\frac{d\tilde{y}(\vartheta)}{dw} = -\zeta \frac{\tilde{\Omega}(\vartheta)\left[1 + \frac{\eta}{\gamma}(1-\tilde{\Omega}(\vartheta))\right] - \left(\frac{dp}{dw} + \frac{dy}{\lambda dw}\right)(1+\frac{\epsilon}{\gamma}\tilde{\Omega}(\vartheta))}{1+\frac{\epsilon}{\gamma}\tilde{\Omega}(\vartheta)\left[1+\zeta(\gamma+\eta(1-\tilde{\Omega}(\vartheta)))\right]}, \quad (52)$$

where we have used the definitions $\eta \equiv (1-\sigma)\epsilon$, and where $dp/dw$ and $dy/dw$ are the responses of the aggregate price index and output to the change in the relative price of IT.$^{94}$

Lemma 5 shows that the heterogeneity across firms in their responses of both IT intensity and market share only depends on their initial IT intensity $\tilde{\Omega}(\vartheta)$. Due to the CES property of the production function, the response of IT intensity is proportional to $1-\sigma$, where $\sigma$ is the elasticity of substitution between IT and non-IT inputs. In addition to this substitution, the response of IT intensity in Equation (51) partly depends on the response of the firm's output due to nonhomotheticity: if a firm's output grows, then its IT intensity rises. Equation (52) shows that, to the first order of approximation, the pass-through from IT price to the firm prices is in line with Equation (60) and proportional to the IT intensity $\tilde{\Omega}(\vartheta)$ of firms. However, for firms with larger IT intensity $\tilde{\Omega}(\vartheta)$, the full response is more complicated since the marginal cost function nonlinearly varies both in IT prices and in the size of the firm.

Using the results of Lemma 5, the following proposition characterizes the within and across firm components of the response of the aggregate IT cost share.

**Proposition 2.** Assume that the ratio of fixed to average costs is small, i.e., $\psi/\bar{C} \ll 1$ and define:

$$\overline{\Omega^n} \equiv \iint \left[ \frac{\tilde{\Omega}^n(\vartheta)}{1 + \frac{\epsilon}{\gamma} \tilde{\Omega}(\vartheta) \left[ 1 + \zeta \left( \gamma + \eta \left( 1 - \tilde{\Omega}(\vartheta) \right) \right) \right]} \right] \Lambda(\vartheta) d^2\vartheta, \quad \text{for } 0 \le n \le 3, \quad (53)$$

<footnote>$^{94}$See the proof of this lemma and the next proposition in Section 1.4 of the online appendix.</footnote>
Then, the within and across firm effects in Equation (30) are given by

$$ \text{Within-firm effect} = (1 - \sigma) \left[ 1 + \zeta \epsilon \left( \frac{dp}{dw} + \frac{dy}{\lambda dw} \right) \right] \left[ \overline{\Omega} - \overline{\Omega^2} + \frac{\epsilon}{\gamma} \left( \overline{\Omega^2} - \overline{\Omega^3} \right) \right], \quad (54) $$

$$ \text{Across-firm effect} = \left[ 1 + \zeta \epsilon \left( \frac{dp}{dw} + \frac{dy}{\lambda dw} \right) \right] \left[ \frac{\lambda - 1}{\lambda \epsilon} \left( \overline{\Omega} + \frac{\epsilon \overline{\Omega^2}}{\gamma} - \overline{\Omega} \left( \overline{\Omega^0} + \frac{\epsilon \overline{\Omega}}{\gamma} \right) \right) \right. \\ \left. + \frac{\eta}{\gamma} \left( \overline{\Omega^2} - \overline{\Omega^3} - \overline{\Omega} \left( \overline{\Omega} - \overline{\Omega^2} \right) \right) \right], \quad (55) $$

where the latter term ignores the terms first-order in $\psi/\overline{C}$.

To unpack the different terms in Equations (54) and (55), let us first examine the special case of homothetic CES production functions.

**Corollary 2.** In the case of a homothetic production function, $\epsilon = 0$, the within and across firm effects in Equation (30) are given by

$$ \text{Within-firm effect} = (1 - \sigma)(\overline{\Omega} - \overline{\Omega^2}), \quad (56) $$

$$ \text{Across-firm effect} = -(\gamma\zeta - 1)(\overline{\Omega^2} - \overline{\Omega^2}). \quad (57) $$

Equations (56) and (57) show that the signs of the two components critically depend on whether the two elasticities of substitution $\sigma$ and $\lambda$ exceed unity. In particular, when $\sigma < 1$ and $\lambda > 1$ the within-firm effect is positive while the across-firm is negative. The equations also generalize the results of Oberfield and Raval (2014) and Baqaee and Farhi (2018) to a non-CRS case. In particular, they show that if there are increasing returns to scale, $\gamma < 1$, the reallocation response is greater compared to the CRS case, and the reverse holds if there are decreasing returns, $\gamma > 1$. As with the CRS case, the relative size of the two components depends on the dispersion of IT intensity, as captured in the factor-payment-weighted variance of the IT cost share, $\overline{\Omega^2} - \overline{\Omega^2}$.

Comparing the results of Corollary 2 with those in the general case in Proposition 2, we first note that Equation (53) defines the four moments that account for the nonlinearities in the marginal cost function that stem from the nonhomotheticity. In addition, we find that in the nonhomothetic case, $\epsilon \neq 0$, the general equilibrium effect on the average firm's output affects the response. This effect is captured by the term $dp/dw + dy/\lambda dw$ in Equations (54) and (55) and implies a larger responses of the aggregate IT intensity to a fall in IT price relative to a CES benchmark if $\eta = (1 - \sigma)\epsilon > 0$. Due to nonhomotheticity of IT demand, a change in factor prices that results in a larger average firm size leads to higher IT intensity for the average firm.

**Partial Equilibrium Analysis** In the remainder of this section, we provide a partial equilibrium analysis that aims to illustrate the different channels through which the presence of nonhomotheticity of IT demand modifies the aggregate response. Let us first examine the within-firm response of the IT cost share $\tilde{\Omega}(\vartheta)$. The results of above show that:

$$ \left. \frac{\partial \tilde{\Omega}(\vartheta)}{\partial w} \right|_{(P,Y)\text{const.}} = \tilde{\Omega}(\vartheta) (1 - \tilde{\Omega}(\vartheta)) \left[ 1 - \underbrace{\left( \sigma - (1 - \sigma) \epsilon \frac{\partial \tilde{\gamma}(\vartheta)}{\partial w} \right)}_{(P,Y)\text{const.}} \right], \quad (58) $$
where we have defined an effective firm-level elasticity of substitution $\tilde{\sigma}(\vartheta)$, relying on the parallel between Equations (58) and (29).<fnref n="95" /> In addition, we have defined the elasticity of output with respect to the relative price of IT, i.e., $\partial\tilde{y}(\vartheta)/\partial w \equiv \partial\log\tilde{Y}(\vartheta)/\partial w$. If the fall in IT prices raises the output of a firm, i.e., $\partial\tilde{y}(\vartheta)/\partial w < 0$, Equation (58) implies that nonhomotheticity ($\epsilon > 0$) leads to a higher effective elasticity of substitution in shaping the within-firm effect in Equation (30). Moving to the across-firm effect, the partial equilibrium response of the density of factor payments $\Lambda_C(\vartheta)$ is also directly tied to the elasticity of firm output through:

$$ \left. \frac{\partial \Lambda_C(\vartheta)}{\partial w} \right|_{(P,Y,g)\text{const.}} \approx \left. \frac{\lambda - 1}{\lambda} \Lambda_C(\vartheta) \frac{\partial \tilde{y}(\vartheta)}{\partial w} \right|_{(P,Y)\text{const.}} \quad (59) $$

where we have assumed that the IT cost share is small, $\tilde{\Omega}(\vartheta) \ll 1$. Therefore, the effect of nonhomotheticity on the response of output, $\partial\tilde{y}(\vartheta)/\partial w$, determines both the within-firm response (in Equation 58) and the across-firm response (in Equation 59).

Let us now examine the variations across firms in the elasticity of output with respect to IT prices. To the first order of approximation in IT cost share $\tilde{\Omega}(\vartheta)$, the elasticity is given by:

$$ \left. \frac{\partial \tilde{y}(\vartheta)}{\partial w} \right|_{(P,Y)\text{const.}} \approx -\zeta \left( 1 + \frac{(1-\sigma)\epsilon}{\gamma} \right) \tilde{\Omega}(\vartheta). \quad (60) $$

A fall in the relative price of IT lowers the average cost of each firm proportionally to its IT cost share $\tilde{\Omega}(\vartheta)$, which in turn raises the output with an adjusted demand elasticity $\zeta = \frac{\lambda}{1+\lambda(\gamma-1)}$. But this shock also raises the returns to scale, lowering the cost elasticity and the gap between marginal and average costs. Therefore, the pass-through of a fall in IT prices to the marginal cost of firms is higher due to the effect on their returns to scale. Equation (60) shows that this channel raises the elasticity of firm output to IT prices compared to the homothetic case by a factor of $(1-\sigma)\epsilon/\gamma$. Finally, the nonhomotheticity of IT demand and the resulting cross-sectional correlation between size and IT cost share shown in Equation (24), in combination with Equation (60), predict that the response of output is greater for larger firms. Therefore, the IT shock reallocates market shares toward larger firms and raises market concentration.

## D Calibration Strategy

We use the results of Table 2 corresponding to the pooled sample of all industries for the parameters of the production function ($\epsilon, \sigma, \gamma$), and the Markov process $\rho = (\rho_{\theta\theta}, \rho_{\theta\phi}, \rho_{\phi\theta}, \rho_{\phi\phi}, \eta_{\theta}, \eta_{\phi})$.<fnref n="96" /> The first and second sets of rows in Table 3 revisit the values of these parameters. The table indicates the parameters that are directly estimated with “Estimated.”

We can determine some of the remaining model parameters based on the estimation results despite the fact that

<footnote n="95">⁹⁵We emphasize that the standard definition of the elasticity of substitution focuses on substitution patterns along a given isoquant. In this sense, as the name nhCES suggests, the elasticity of substitution here remains constant and equal to $\sigma$ for all firms. The partial derivatives in the definition in Equation (58) additionally include the response of the firm output, keeping constant all general equilibrium variables except the relative price of IT.</footnote>

<footnote n="96">⁹⁶The only remaining parameter from Table 2 used for this exercise is the parameter $\alpha$ used for the patterns of labor share. As we explain below, we use the parameter $\alpha$ corresponding to the estimates from the manufacturing sector. The estimated values of the time-trend parameters $(\mu_{\theta}, \mu_{\phi})$ are negligible and we set them to zero, in line with the stationary structure of the equilibrium of the model developed in Section 3.3.</footnote>
they have not been directly estimated. In particular, the estimation results allow us to infer the values of the factor symmetric and IT-biased productivity states $\vartheta_{it} = (\theta_{it}, \phi_{it})$ from Equations (32) and (33) and the productivity innovations $u_{it} = (u_{\theta,it}, u_{\phi,it})$ through Equation (31) for each firm $i$ at time $t$ in the data. We use the inferred productivity innovations to find estimated values for the variances $(x_{\theta}^2, x_{\phi}^2)$ of the two productivity innovations. The last row in the parameters of the productivity process in Table 3 presents the values of these variance parameters. The table indicates the parameters that we have determined indirectly based on the results of estimation with "Estimation."

The inferred values of productivity states further allow us to calibrate the distribution $F$ of the productivity states of entrants in Equation (39). We rely on the productivity states inferred from the estimation to calibrate the parameters $(\xi_o, \bar{\theta}_o)$. Given the Pareto assumption and the independence of distributions of $\theta$ and $\phi$ in $F$, the right tail of the distribution of factor-symmetric productivity states must correspond to the largest entrants that we observe in our data. Therefore, we can infer the behavior of the tail of the distribution based on the estimated $\theta$s among the largest entrants (firms younger than one year). Similarly, we calibrate the variance $x_o^2$ of the distribution of IT-biased productivity states among entrants from data. Table 3 shows the values of these parameters that are found based on the estimation results. The remaining two parameters $\underline{\theta}_o$ and $\bar{\phi}_o$ of the distribution $F$ require the knowledge of the entire distribution of productivity states. Since there is some selection toward larger firms in the sample we use for estimation, we do not rely on our estimation results to calibrate these two parameters. We will shortly return to these parameters below.

Several model parameters can be directly matched to observable moments in the data, or values reported in prior work. Table 3 indicates the values of these parameters as “Calibrated.” For the exogenous probability of exit, we calibrate its value to the average rate of exit of large firms in our sample of around $\delta = 0.04$. We calibrate the cost of entry $\chi$ to fit the number of firms per worker in our data ($N \approx 0.08$), given all other parameters of the model. These two parameters appear in the last two rows of the parameters of the process of entry and exit. Finally, we set the discount rate to $\rho = 0.95$ and the elasticity of substitution among different firm products to $\lambda = 5$, values commonly assumed in the literature.

We are left with a set of three parameters $(\psi, \underline{\theta}_o, \bar{\phi}_o)$, including the fixed cost of operation $\psi$, and two parameters $\underline{\theta}_o$ and $\bar{\phi}_o$ corresponding to the distribution $F$ of entrants. To calibrate these remaining parameters, we perform a search in the parameter space, targeting the following three data moments in year 1995: two measures of market concentration (the share of top 1% and 5% of firms in total sales) and aggregate IT intensity $\bar{\Omega}/(1+\psi/\bar{C})$.<fnref n="97" /> We use our firm-level data to calculate the first two data moments based on the pooled sample of BRN and RSI firms. For the last data moment, we rely on the macro data series to find the aggregate IT intensity. We cannot rely on the sample of EAE firms to calculate the aggregate IT intensity since the sample covers firms above a size threshold and is not representative of all firms. Table 3 indicates the three parameters calibrated based on this moment matching strategy with “Search.”

<footnote n="97">⁹⁷We begin the search with the following values: we use $\psi = 0$ and for $(\underline{\theta}_o, \bar{\phi}_o)$ we use the lower bound and the mean of the corresponding estimates in our sample of entrants. We describe the search procedure and the calibration of the productivity distributions with greater details in Section 5 of the online appendix.</footnote>
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<table><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 marché du travail</td></tr><tr><td>G 9912</td><td>Ch. GIANELLA<br/>Une estimation de l'élasticité de l'emploi peu qualifié à son coût</td></tr><tr><td>G 9913</td><td>Division « Redistribution et Politiques Sociales »<br/>Le modèle de microsimulation dynamique DESTINIE</td></tr><tr><td>G 9914</td><td>E. DUGUET<br/>Macro-commandes SAS pour l'économie des panellés et des variables qualitatives</td></tr><tr><td>G 9915</td><td>R. DUHAUTOIS<br/>Évolution du flux d'emplois en France entre 1990 et 1996 : une étude empirique à partir du 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 Baxter et King</td></tr><tr><td>G 9917</td><td>B. CREPON - R. DESPLATZ - J. MAIREsse<br/>Estimating price cost margins, scale economies 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 function: an evaluation on a panel of French firms from the manufacturing sector</td></tr><tr><td>G 9919</td><td>S. AUDRIC - P. GIVORD - C. PROST<br/>Évolution de l'emploi et des coûts par qualification entre 1982 et 1996</td></tr><tr><td>G 2000/01</td><td>R. MAHIEU<br/>Les déterminants des dépenses de santé : une approche macroéconomique</td></tr><tr><td>G 2000/02</td><td>C. ALLARD-PRIGENT - H. GUILMEAU - A. QUINET<br/>The real return rate as the relative price of nontrades in terms of tradables: theoretical 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 par Christiano et Fitzgeral</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 poids du cycle</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 de la retirement decision: a supply side approach</td></tr><tr><td>G 2000/08</td><td>C. AUDENIS - C. PROST<br/>Déficit conjointement : une prise en compte des conjonctures passées</td></tr><tr><td>G 2000/09</td><td>R. MAHIEU - B. SÉDILLOT<br/>Équivalent patrimonial de la rente et souscription de retraite complémentaire</td></tr></table>
<table><tr><td>G 2000/10</td><td>R. DUHAUTOIS</td><td>Ralentissement de l'investissement : petites ou grandes entreprises ? industrie ou tertiaire ?</td></tr><tr><td>G 2000/11</td><td>G. LAROQUE - B. SALANIÉ</td><td>Temps partiel féminin et incitations financières à l'emploi</td></tr><tr><td>G 2000/12</td><td>Ch. GIANELLA</td><td>Local unemployment and wages</td></tr><tr><td>G 2000/13</td><td>B. CREPON - Th. HECKEL</td><td>Informatisation en France ; une évaluation à partir de données individuelles</td></tr><tr><td>G 2001/01</td><td>F. LEQUILLER</td><td>- La nouvelle économie et la mesure de la croissance du PIB<br/>- The new economy and the measure ment of GDP growth</td></tr><tr><td>G 2001/02</td><td>S. AUDRIC</td><td>La reprise de la croissance de l'emploi profite-t-elle aussi aux non-diplômés ?</td></tr><tr><td>G 2001/03</td><td>I. BRAUN-LEMAIRE</td><td>Évolution et repartition du surplus de productivité</td></tr><tr><td>G 2001/04</td><td>A. BEAUDU - Th. HECKEL</td><td>Le canal du crédit fonctionne-t-il en Europe ? Une étude de l'ethanoléfaction des comportements d'investissement à partir de données de bilan agregées</td></tr><tr><td>G 2001/05</td><td>C. AUDENIS - P. BISCOURP - N. FOURCADE - O. LOISE</td><td>Testing the augmented Solow growth model: An empirical reassessment using panel data</td></tr><tr><td>G 2001/06</td><td>R. MAHIEU - B. SÉDILLOT</td><td>Départ à la retraite, irréversibilité et incertitude</td></tr><tr><td>G 2001/07</td><td>Bilan des activités de la DESE - 2000</td><td></td></tr><tr><td>G 2001/08</td><td>J. Ph. GAUDEMET</td><td>Les dispositifs d'acquisition à titre facultatif d'annuities viagères de retraite</td></tr><tr><td>G 2001/09</td><td>B. CREPON - Ch. GIANELLA</td><td>Fiscalité, coût d'usage du capital et demande de facteurs : une analyse sur données individuelles</td></tr><tr><td>G 2001/10</td><td>B. CRÉPON - R. DESPLATZ</td><td>Évaluation des effets des dispositifs d'allégements</td></tr><tr><td>G 2001/11</td><td>J.-Y. FOURNIER</td><td>Comparaison des salaires des secteurs public et privé</td></tr><tr><td>G 2001/12</td><td>J.-P. BERTHIER - C. JAULENT</td><td>R. CONVENEVOLE - S. PISANI</td></tr><tr><td>G 2001/13</td><td>P. BISCOURP - Ch. GIANELLA</td><td>Substitution and complementarity between capital, skilled and less skilled workers: an analysis at the firm level in the French manufacturing industry</td></tr><tr><td>G 2001/14</td><td>I. ROBERT-BOBÉE</td><td>Modeling demographic behaviours in the French</td></tr></table>

<table><tr><td>G2002/13</td><td>M. LECLAIR</td><td>Réduction du temps de travail et tensions sur les facteurs de production</td></tr><tr><td>G2002/14</td><td>E. WALRAET - A. VINCENT</td><td>- Analysis of the redistribution intragénérationnelle dans le système de retraites des salariés du privé</td></tr><tr><td>G2002/15</td><td>P. CHONE - D. LE BLANC - I. ROBERT-BOBEE</td><td>- Une approche par microsimulation</td></tr><tr><td>G2002/16</td><td>P. MAUREL - S. GREGOIR</td><td>- Intragenerational distributional analysis in the french private sector pension scheme - A microsimulation approach</td></tr><tr><td>G2003/01</td><td>N. RIEDINGER - E. HAUVY</td><td>Le coût de dépilation atmosphérique pour les entreprises françaises : une estimation à partir de données individuelles</td></tr><tr><td>G2003/02</td><td>P. BISCOURP et F. KRAMARZ</td><td>Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises : une analyse sur la période 1986-1992</td></tr><tr><td>G2003/03</td><td>Bilan des activités de la DESE - 2002</td><td></td></tr><tr><td>G2003/04</td><td>P.-O. BEFFY - J. DEROYON - N. FOURCADE - S. GREGOIR - N. LAIB - B. MONFORT</td><td>Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020</td></tr><tr><td>G2003/05</td><td>P. AUBERT</td><td>La situation des salariés de plus de cinquante ans dans le secteur privé</td></tr><tr><td>G2003/06</td><td>P. AUBERT - B. CRÉPON</td><td>Age, salaire et productivité</td></tr><tr><td>G2003/07</td><td>H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU</td><td>La productivité des salariés décline-t-elle en fin de carrière ?</td></tr><tr><td>G2003/08</td><td>P. BISCOURP - N. FOURCADE</td><td>Le renaltissement de la productivité du travail au cours des années 1990</td></tr><tr><td>G2003/09</td><td>P. BISCOURP - N. FOURCADE</td><td>Patrimoine des ménages, dynamique d'allocation et comportement de consommation</td></tr><tr><td>G2003/10</td><td>P. BISCOURP - N. FOURCADE</td><td>Peu-on mettre en évidence l'existence de rigidités à la basse des salaires à partir de données individuelles ? Le cas de la France à la fin des années 90</td></tr><tr><td>G2003/11</td><td>M. LECLAIR - P. PETIT</td><td>Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes ?</td></tr><tr><td>G2003/12</td><td>P. BISCOURP - N. FOURCADE</td><td>Parages - B. MONFORT</td></tr><tr><td>G2004/01</td><td>P. AUBERT - M. LECLAIR</td><td>La compétitivité exprimée dans les enquêtes trimestrielles sur la situation et les perspectives dans l'industrie</td></tr></table>

<table><tr><td>G2002/13</td><td>M. LECLAIR</td><td>Réduction du temps de travail et tensions sur les facteurs de production</td></tr><tr><td>G2002/14</td><td>E. WALRAET - A. VINCENT</td><td>- Analysis of the redistribution intragénérationnelle dans le système de retraites des salariés du privé</td></tr><tr><td>G2002/15</td><td>P. CHONE - D. LE BLANC - I. ROBERT-BOBEE</td><td>- Une approche par microsimulation</td></tr><tr><td>G2002/16</td><td>P. MAUREL - S. GREGOIR</td><td>- Les indices de compétitivité des pays : inter- prétation et limites</td></tr><tr><td>G2003/01</td><td>N. RIEDINGER - E. HAUVY</td><td>Le coût de dépilation atmosphérique pour les entreprises françaises : une estimation à partir de données individuelles</td></tr><tr><td>G2003/02</td><td>P. BISCOURP et F. KRAMARZ</td><td>Création d'emplois, destruction d'emplois et internationalisation des entreprises industrielles françaises : une analyse sur la période 1986-1992</td></tr><tr><td>G2003/03</td><td>Bilan des activités de la DESE - 2002</td><td></td></tr><tr><td>G2003/04</td><td>P.-O. BEFFY - J. DEROYON - N. FOURCADE - S. GREGOIR - N. LAIB - B. MONFORT</td><td>Évolutions démographiques et croissance : une projection macro-économique à l'horizon 2020</td></tr><tr><td>G2003/05</td><td>P. AUBERT</td><td>La situation des salariés de plus de cinquante ans dans le secteur privé</td></tr><tr><td>G2003/06</td><td>P. AUBERT - B. CRÉPON</td><td>Age, salaire et productivité</td></tr><tr><td>G2003/07</td><td>H. BARON - P.O. BEFFY - N. FOURCADE - R. MAHIEU</td><td>La productivité des salariés décline-t-elle en fin de carrière ?</td></tr><tr><td>G2003/08</td><td>P. BISCOURP - N. FOURCADE</td><td>Patrimoine des ménages, dynamique d'allocation et comportement de consommation</td></tr><tr><td>G2003/09</td><td>P. BISCOURP - N. FOURCADE</td><td>Peu-on mettre en évidence l'existence de rigidités à la basse des salaires à partir de données individuelles ? Le cas de la France à la fin des années 90</td></tr><tr><td>G2003/10</td><td>M. LECLAIR - P. PETIT</td><td>Présence syndicale dans les firmes : quel impact sur les inégalités salariales entre les hommes et les femmes ?</td></tr><tr><td>G2003/11</td><td>P. BISCOURP - N. FOURCADE</td><td>Parages - B. MONFORT</td></tr><tr><td>G2004/01</td><td>P. AUBERT - M. LECLAIR</td><td>La compétitivité exprimée dans les enquêtes trimestrielles sur la situation et les perspectives dans l'industrie</td></tr></table>

<table><tr><td>G2004/02</td><td>M. DUÉE - C. REBILLARD</td><td>La dépendance des personnes âgées : une projection à long terme</td></tr><tr><td>G2004/03</td><td>S. RASPILLER - N. RIEDINGER</td><td>Réglation environnementale et choix de localisation des groupes français</td></tr><tr><td>G2004/04</td><td>A. NABOULET - S. RASPILLER</td><td>Les déterminants de la décision d'investir : une approche par les perceptions subjectives les firmes</td></tr><tr><td>G2004/05</td><td>N. RAGACHE</td><td>La déclaration des enfants par les couples non mariés est-elle fiscalement optimale ?</td></tr><tr><td>G2004/06</td><td>M. DUÉE</td><td>L'impact du chomage des parents sur le devenir scolaire des enfants</td></tr><tr><td>G2004/07</td><td>P. AUBERT - E. CAROLI - M. ROGER</td><td>New Technologies, Workplace Organisation and the Age Structure of the Workforce: Firm-Level Evidence</td></tr><tr><td>G2004/08</td><td>E. DUGUET - C. LELARGE</td><td>Les brevets accroissent-ils les incitations privées à innover ? Un examen microéconométrique</td></tr><tr><td>G2004/09</td><td>S. RASPILLER - P. SILLARD</td><td>Affiliating versus Subcontracting: The Case of Multinationals</td></tr><tr><td>G2004/10</td><td>J. BOISSINOT - C. L'ANGEVIN - B. MONFORT</td><td>Public Debt Sustainability: Some Results on the French Case</td></tr><tr><td>G2004/11</td><td>S. ANANIAN - P. AUBERT</td><td>Travailleurs âgés, nouvelles technologies et changements organisationnels; un réexamen à partir de l'enquête « REPONSE »</td></tr><tr><td>G2004/12</td><td>X. BONNET - H. PONCET</td><td>Structures de revenus et propensions différentes à consommer - Vers une équation de consommation des ménages plus robuste en prévision pour la France</td></tr><tr><td>G2004/13</td><td>C. PICART</td><td>Évaluer la rentabilité des sociétés non financières</td></tr><tr><td>G2004/14</td><td>J. BARDAJI - B. SÉDILLOT - E. WALRAET</td><td>Les retraites du secteur public: projections à l'horizon 2040 à l'aide du modèle de microsimulation DESTINE</td></tr><tr><td>G2005/01</td><td>S. RUFFEATEAU - P. GODEFOY</td><td>Conditions de départ en retraite selon l'âge de fin d'études : analyse prospective pour les générations 1945 à 1974</td></tr><tr><td>G2005/02</td><td>C. AFSA - S. BUFFETEAU</td><td>L'évolution de l'activité féminine en France : une approche par pseudo-panel</td></tr><tr><td>G2005/03</td><td>P. AUBERT - P. SILLARD</td><td>Délocalisations et réductions d'effectifs dans l'industrie française</td></tr><tr><td>G2005/04</td><td>M. LECLAIR - S. ROUX</td><td>Mesure et utilisation des emplois instables dans les entreprises</td></tr><tr><td>G2005/05</td><td>C. L'ANGEVIN - S. SERRAVALLE</td><td>Performances à l'exportation de la France et de l'Allemagne - Une analyse par secteur et de l'industrie géographique</td></tr></table>
<table><tr><td>G2005/06</td><td>Bilan des activités de la Direction des Études et Syntheses Économiques - 2004</td></tr><tr><td>G2005/07</td><td>S. RASPILLER<br/>La concurrence fiscale : principaux enseignements de l'analyse économique</td></tr><tr><td>G2005/08</td><td>C. LANGEVIN - N. LAÎB<br/>Éducation et croissance en France et dans un panel de 21 pays de l'OCDE</td></tr><tr><td>G2005/09</td><td>N. FERRARI<br/>Prévoir l'investissement des entreprises<br/>Un indicateur des révisions dans l'enquête de conjoncture sur les investissements dans l'industrie</td></tr><tr><td>G2005/10</td><td>P.-O. BEFFY - C. LANGEVIN<br/>Chomage et boucle prix-salaires:<br/>apport d'un modèle « qualifiés/peu qualifiés »</td></tr><tr><td>G2005/11</td><td>B. HEITZ<br/>A two-states Markov-switching model of inflation in France and the USA: credible target VS inflation spiral</td></tr><tr><td>G2005/12</td><td>O. BIAU - H. ERKEL-ROUSSE - N. FERRARI<br/>Réponses individuelles aux enjeux de conjoncture et prévision macroéconomiques:<br/>Exemple de la prévision de la production manufacturière</td></tr><tr><td>G2005/13</td><td>P. AUBERT - D. BLANCHET - D. BLAU<br/>The labour market after age 50: some elements of a Franco-American comparison</td></tr><tr><td>G2005/14</td><td>D. BLANCHET - T. DEBRAND - P. DOURGNON - P. POLLET<br/>L'enquête SHARE: presentation et premiers résultats de l'édition française</td></tr><tr><td>G2005/15</td><td>M. DUÉ<br/>La modélisation des comportements démographiques dans le modèle de microsimulation DESTINE</td></tr><tr><td>G2005/16</td><td>H. RAQUI - S. ROUX<br/>Étude de simulation sur la participation versée aux salariés par les entreprises</td></tr><tr><td>G2006/01</td><td>C. BONNET - S. BUFFETEAU - P. GODEFROY<br/>Disparités de retraite de droit direct entre hommes et femmes: quelles évolutions ?</td></tr><tr><td>G2006/02</td><td>C. PICART<br/>Les gazelles en France</td></tr><tr><td>G2006/03</td><td>P. AUBERT - B. CRÉPON - P. ZAMORA<br/>Le rendement apparent de la formation continue dans les entreprises : effets sur la productivité et des salaires</td></tr><tr><td>G2006/04</td><td>J.-F. OUVRARD - R. RATHELOT<br/>Demographic change and unemployment:<br/>what do macroeconomic models predict?</td></tr><tr><td>G2006/05</td><td>D. BLANCHET - J.-F. OUVRARD<br/>Indicateurs d'engagements implicites des systèmes de retraite: chiffrages, propriétés analytiques et réactions à des chocs démographiques types</td></tr><tr><td>G2006/06</td><td>G. BIAU - O. BIAU - L. ROUVIERE<br/>Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data</td></tr></table>

<table><tr><td>G2006/07</td><td>C. AFSA - P. GIVORD<br/>Le rôle des conditions de travail dans les absences pour maladie</td></tr><tr><td>G2006/08</td><td>P. SILLARD - C. LANGEVIN - S. SERRAVALLE<br/>Performances comparées à l'exportation de la France et de ses principaux partenaires</td></tr><tr><td>G2006/09</td><td>Une analyse structurelle sur 12 ans</td></tr><tr><td>G2006/10</td><td>X. BOUTIN - S. QUANTIN<br/>Une méthodologie d'évaluation comptable du coût du capital des entreprises françaises : 1984-2002</td></tr><tr><td>G2006/11</td><td>C. AFSA<br/>L'estimation d'un coût implicite de la pénibilité du travail chez les travailleurs âgés</td></tr><tr><td>G2006/12</td><td>C. LELARGE<br/>Les entreprises (industrielles) françaises sont-elles à la frontière technologique ?</td></tr><tr><td>G2006/13</td><td>O. BIAU - N. FERRARI<br/>Théorie de l'opinion<br/>Faut-il ponderer les réponses individuelles ?</td></tr><tr><td>G2006/14</td><td>A. KOUBI - S. ROUX<br/>Une réinterprétation de la relation entre productivité et inégalités salariales dans les entreprises</td></tr><tr><td>G2006/15</td><td>R. RATHELOT - P. SILLARD<br/>The impact of local taxes on plants location decision</td></tr><tr><td>G2006/16</td><td>L. GONZALEZ - C. PICART<br/>Diversification, recentrage et poids des activités de support dans les groupes (1993-2000)</td></tr><tr><td>G2006/17</td><td>D. SRAER<br/>Allegements de cotisations patronales et dynamique salariale</td></tr><tr><td>G2006/18</td><td>V. ALBOUY - L. LEGUIEN<br/>Les rendements non monétaires de l'éducation : le cas de la santé</td></tr><tr><td>G2006/19</td><td>D. BLANCHET - T. DEBRAND<br/>Aspiration à la retraite, santé et satisfaction au travail : une comparaison européenne</td></tr><tr><td>G2006/20</td><td>M. BARLET - L. CRUSSON<br/>Quel impact des variations du prix du pétrole sur la croissance française ?</td></tr><tr><td>G2006/21</td><td>C. PICART<br/>Flux d'emploi et de main-d'œuvre en France : un réexamen</td></tr><tr><td>G2006/22</td><td>V. ALBOUY - C. TAVAN<br/>Massification et démocratisation de l'enseignement supérieur en France</td></tr><tr><td>G2006/23</td><td>T. LE BARBANCHON<br/>The Changing response to oil price shocks in France: a DSGE type approach</td></tr><tr><td>G2006/24</td><td>T. CHANEY - D. SRAER - D. THESMAR<br/>Collateral Value and Corporate Investment<br/>Evidence from the French Real Estate Market</td></tr><tr><td>G2006/25</td><td>J. BOISSINOT<br/>Consumption over the Life Cycle: Facts for France</td></tr><tr><td>G2006/26</td><td>C. AFSA<br/>Interpréter les variables de satisfaction : l'exemple de la durée du travail</td></tr></table>

<table><tr><td>G2007/11</td><td>R. RATHELOT - P. SILLARD<br/>Zones Franches Urbaines : quels effets sur l'emploi salaré et les créations d'établissements ?</td></tr><tr><td>G2007/12</td><td>V. ALBOUY - B. CRÉPON<br/>Aléa moral en santé: une évaluation dans le cadre du modèle causal de Rubin</td></tr><tr><td>G2008/01</td><td>C. PICART<br/>Les PME françaises : rentables mais peu dynamiques</td></tr><tr><td>G2008/02</td><td>P. BISCOURP - X. BOUTIN - T. VERGÉ<br/>The Effects of Retail Regulations on Prices<br/>Evidence form the Loi Galland</td></tr><tr><td>G2008/03</td><td>Y. BARBESOL - A. BRIANT<br/>Économies d'agglomération et productivité des entreprises: estimation sur données individuelles françaises</td></tr><tr><td>G2008/04</td><td>D. BLANCHET - F. LE GALLO<br/>Les projections démographiques: principaux mécanismes et retour sur l'expérience française</td></tr><tr><td>G2008/05</td><td>D. BLANCHET - F. TOUTLEMONDE<br/>Évolutions démographiques et deformation du cycle de vie active: quelles relations ?</td></tr><tr><td>G2008/06</td><td>M. BARLET - D. BLANCHET - L. CRUSSON<br/>Internationalisation et flux d'emplois: que doit une approche comptable ?</td></tr><tr><td>G2008/07</td><td>C. LELARGE - D. SRAER - D. THESMAR<br/>Entrepreneurship and Credit Constraints - Evidence from a French Loan Guarantee Program</td></tr><tr><td>G2008/08</td><td>X. BOUTIN - L. JANIN<br/>Are Prices Really Affected by Mergers?</td></tr><tr><td>G2008/09</td><td>M. BARLET - A. BRIANT - L. CRUSSON<br/>Concentration géographique dans l'industrie manufacturière et dans les services en France: une approche par un indicateur en continu</td></tr><tr><td>G2008/10</td><td>M. BEFFY - É. COUDIN - R. RATHELOT<br/>Who is confronted to insecure labor market histories? Some evidence based on the French labor market transition</td></tr><tr><td>G2008/11</td><td>M. ROGER - E. WALRAET<br/>Social Security and Well-Being of the Elderly: the Case of France</td></tr><tr><td>G2008/12</td><td>C. AFSA<br/>Analyser les composantes du bien-être et de son évolution<br/>Une approche empirique sur données individuelles</td></tr><tr><td>G2008/13</td><td>M. BARLET - D. BLANCHET - T. LE BARBANCHON<br/>Microsimuler le marché du travail: un prototype</td></tr><tr><td>G2008/14</td><td>P.-A. PIONNIER<br/>Le partage de la valeur ajoutée en France, 1949-2007</td></tr><tr><td>G2008/15</td><td>La modélisation des comportements démographiques dans le modèle de microsimulation DESTINE</td></tr><tr><td>G2008/16</td><td>M. DUÉ<br/>La modélisation des comportements démographiques dans le modèle de microsimulation DESTINE</td></tr><tr><td>G2008/17</td><td>H. RAQUI - S. ROUX<br/>Étude de simulation sur la participation versée aux salariés par les entreprises</td></tr><tr><td>G2008/18</td><td>C. BONNET - S. BUFFETEAU - P. GODEFROY<br/>Disparités de retraite de droit direct entre hommes et femmes: quelles évolutions ?</td></tr><tr><td>G2008/19</td><td>C. PICART<br/>Les gazelles en France</td></tr><tr><td>G2008/20</td><td>P. AUBERT - B. CRÉPON - P. ZAMORA<br/>Le rendement apparent de la formation continue dans les entreprises: effets sur la productivité et des salaires</td></tr><tr><td>G2008/21</td><td>J.-F. OUVRARD - R. RATHELOT<br/>Demographic change and unemployment:<br/>what do macroeconomic models predict?</td></tr><tr><td>G2008/22</td><td>D. BLANCHET - J.-F. OUVRARD<br/>Indicateurs d'engagements implicites des systèmes de retraite: chiffrages, propriétés analytiques et réactions à des chocs démographiques types</td></tr><tr><td>G2008/23</td><td>G. BIAU - O. BIAU - L. ROUVIERE<br/>Nonparametric Forecasting of the Manufacturing Output Growth with Firm-level Survey Data</td></tr></table>

<table><tr><td>G2009/04</td><td>P. GIVORD - L. WILNER<br/>Les contrats temporaires: trappe ou marchéped vers l'emploi stable ?</td></tr><tr><td>G2009/05</td><td>G. LALANNE - P.-A. PIONNIER - O. SIMON<br/>Le partage des fruits de la croissance de 1950 à 2008: une approche par les comptes de surplus</td></tr><tr><td>G2009/06</td><td>L. DAVEZIES - X. D'HAULTFEOUILLE<br/>Faut-il ponderer ?...<br/>Ou l'étoileme question de l'économie confrontée à des données d'enquête</td></tr><tr><td>G2009/07</td><td>S. QUANTIN - S. RASPILLER - S. SERRAVALLE<br/>Commerce intragroupe: fiscalité et prix de transferts: une approche sur données françaises</td></tr><tr><td>G2009/08</td><td>M. CLERC - V. MARCUS<br/>Élastiques-prix des consommations énergétiques des ménages</td></tr><tr><td>G2009/09</td><td>G. LALANNE - E. POULIQUEN - O. SIMON<br/>Prix du pétrole et croissance potentielle à long terme</td></tr><tr><td>G2009/10</td><td>D. BLANCHET - J. LE CACHEUX - V. MARCUS<br/>Adjusted net savings and other approaches to sustainability: some theoretical background</td></tr><tr><td>G2009/11</td><td>V. BELLAMY - G. CONSALES - M. FESSEAU - S. LE LADIER - É. RAYNAUD<br/>Une décomposition du compte des ménages de la comptabilité nationale par catégorie de ménage en 2003</td></tr><tr><td>G2009/12</td><td>J. BARDAJI - F. TALLENT<br/>Defecting Economic Regimes in France: a Qualitative Markov-Switching Indicator Using Mixed Frequency Data</td></tr><tr><td>G2009/13</td><td>R. AEBERHARDT - D. FOUGÈRE - R. RATHELOT<br/>Discrimination à l'embauche: comment exploiter les procédures de testing ?</td></tr><tr><td>G2009/14</td><td>Y. BARBESOL - P. GIVORD - S. QUANTIN<br/>Partage de la valeur ajoutée, approche par données microéconomiques</td></tr><tr><td>G2009/15</td><td>I. BUONO - G. LALANNE<br/>The Effect of the Uruguay round on the Intensive and Extensive Margins of Trade</td></tr><tr><td>G2010/01</td><td>C. MINODIER<br/>Avantages comparés des séries des premières valeurs publiées et des séries des valeurs révisées - Un exercice de prévision en temps réel</td></tr><tr><td>G2010/02</td><td>v. la croissance trimestrielle du PIB en France<br/>V. ALBOUY - L. DAVEZIES - T. DEBRAND<br/>Health Expenditure Models: a Comparison of Five Specifications using Panel Data</td></tr><tr><td>G2010/03</td><td>C. KLEIN - O. SIMON<br/>Le modèle MÉSANGE réestimé en base 2000<br/>Tome 1 - Version avec volumes à prix constants</td></tr><tr><td>G2010/04</td><td>M.-É. CLERC - É. COUDIN<br/>L'IPC, miroir de l'évolution du coût de la vie en France ?<br/>Ce qu'apporte l'analyse des courbes d'Engel</td></tr><tr><td>G2010/05</td><td>N. CECI-RENAUD - P.-A. CHEVALIER<br/>Les seuils de 10, 20 et 50 salariés: impact sur la taille des entreprises françaises</td></tr></table>
<table><tr><td>G2010/06</td><td>R. AEBERHARDT - J. POUGET<br/>National Origin Differences in Wages and Hierarchical Positions - Evidence from French Full-Time Male Workers from a matched Employer-Employee Dataset</td></tr><tr><td>G2010/07</td><td>S. BLASCO - P. GIVORD<br/>Les trajectoires professionnelles en début de vie active : quel impact des contrats temporaires ?</td></tr><tr><td>G2010/08</td><td>P. GIVORD<br/>Méthodes économétriques pour l'évaluation de politiques publiques</td></tr><tr><td>G2010/09</td><td>P.-Y. CABANNES - V. LAPEGUE -<br/>E. POULIQUEN - M. BEFFY - M. GAINI<br/>Quelle croissance de moyen terme après la crise?</td></tr><tr><td>G2010/10</td><td>I. BUONO - G. LALANNE<br/>La réaction des entreprises françaises à la baisse des tarifs douanés étrangers</td></tr><tr><td>G2010/11</td><td>R. RATHELOT - P. SILLARD<br/>L'apport des méthodes à noyaux pour mesurer la concentration géographique - Application à la concentration des immigres en France de 1968 à 1999</td></tr><tr><td>G2010/12</td><td>M. BARATON - M. BEFFY - D. FOUGÈRE<br/>Une évaluation de l'effet de la réforme de 2003 sur les départs en retraite - Le cas des enseignants du second degré public</td></tr><tr><td>G2010/13</td><td>D. BLANCHET - S. BUFFETEAU - E. CRENNER<br/>Le modèle de microsimulation Destinie 2 : principes caractéristiques et premiers résultats</td></tr><tr><td>G2010/14</td><td>D. BLANCHET - E. CRENNER<br/>Le bloc retraite du modèle Destinie 2 : guide de l'utilisateur</td></tr><tr><td>G2010/15</td><td>M. BARLET - L. CRUSSON - S. DUPUCH -<br/>F. PUECH<br/>Des services échangés aux services échan-geables : une application sur données françaises</td></tr><tr><td>G2010/16</td><td>M. BEFFY - T. KAMIONKA<br/>Public-private wage gaps: is civil-servant human capital sector-specific?</td></tr><tr><td>G2010/17</td><td>P.-Y. CABANNES - H. ERKEL-ROUSSE -<br/>G. LALANNE - O. MONSO - E. POULIQUEN<br/>Le modèle Mésange réestimé en base 2000</td></tr><tr><td>G2010/18</td><td>Tome 2 - Version avec volumes à prix chaînes<br/>R. AEBERHARDT - L. DAVEZIES<br/>Conditional Logit with one Binary Covariate: Link between the Static and Dynamic Cases</td></tr><tr><td>G2011/01</td><td>T. LE BARBANCHON - B. OURLIAC - O. SIMON<br/>Les marchés du travail français et américain face aux chocs conjonctureux des années 1986 à 2007 : une modélisation DSGE</td></tr><tr><td>G2011/02</td><td>C. MARBOT<br/>Une évaluation de la réduction d'impôt pour l'emploi de salariés à domicile</td></tr><tr><td>G2011/03</td><td>L. DAVEZIES<br/>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</td></tr></table>

<table><tr><td>G2011/04</td><td>M. ROGER - M. WASMER<br/>Heterogeneity matters: labour productivity differentiated by age and skills</td></tr><tr><td>G2011/05</td><td>J.-C. BRICONGNE - J.-M. FOURNIER<br/>V. LAPEGUE - O. MONSO<br/>De la crise financière à la crise économique l'impact des perturbations financières de 2007 et 2008 sur la croissance de sept pays industrialisés</td></tr><tr><td>G2011/06</td><td>P. CHARNOZ - É. COUDIN - M. GAINI<br/>Wage inequalities in France 1976-2004: a quantile regression analysis</td></tr><tr><td>G2011/07</td><td>M. CLERC - M. GAINI - D. BLANCHET<br/>Recommendations of the Suïlitz-Sen-Foussi<br/>Report: A few illustrations</td></tr><tr><td>G2011/08</td><td>M. BACHELET - M. BEFFY - D. BLANCHET<br/>Projeter l'impact des réformes des retraites sur l'activité des 55 ans et plus: une comparaison de trois modèles</td></tr><tr><td>G2011/09</td><td>C. LOUVOT-RUNAVOT<br/>L'évaluation de l'activité dissimulée des entre-prises sur la base des contrôles fiscaux et son insertion dans les comptes nationaux</td></tr><tr><td>G2011/10</td><td>A. SCHREIBER - A. VICARD<br/>La tertiairisation de l'économie française et le ralentissement de la productivité entre 1978 et 2008</td></tr><tr><td>G2011/11</td><td>M.-É. CLERC - O. MONSO - E. POULIQUEN<br/>Les inégalités entre générations depuis le baby-boom</td></tr><tr><td>G2011/12</td><td>C. MARBOT - D. ROY<br/>Évaluation de la transformation de la réduction d'impôt en crédit d'impôt pour l'emploi de salariés à domicile en 2007</td></tr><tr><td>G2011/13</td><td>P. GIVORD - R. RATHELOT - P. SILLARD<br/>Place-based tax exemptions and displacement effects: An evaluation of the Zones Franches Urbanes program</td></tr><tr><td>G2011/14</td><td>X. D'HAULTFOEUILLE - P. GIVORD -<br/>X. BOUTIN<br/>The Environmental Effect of Green Taxation: the Case of the French "BonusMalus"</td></tr><tr><td>G2011/15</td><td>M. BARLET - M. CLERC - M. GARNEO -<br/>V. LAPEGUE - V. MARCUS<br/>La nouvelle version du modèle MZE, modèle macroéconométrique pour la zone euro</td></tr><tr><td>G2011/16</td><td>R. AEBERHARDT - I. BUONO - H. FADINGER<br/>Learning. Incomplete Contracts and Export Dynamics: Theory and Evidence form French Firms</td></tr><tr><td>G2011/17</td><td>C. KERDRAIN - V. LAPÈGUE<br/>Restrictive Fiscal Policies in Europe: What are the Likely Effects?</td></tr><tr><td>G2012/01</td><td>P. GIVORD - S. QUANTIN - C. TREVIEN<br/>A Long-Term Evaluation of the First Generation of the French Urban Enterprise Zones</td></tr><tr><td>G2012/02</td><td>N. CECI-RENAUD - V. COTTET<br/>Politique salariale et performance des entreprises</td></tr><tr><td>G2012/03</td><td>P. FÉVRIER - L. WILNER<br/>Do Consumers Correctly Expect Price Reductions? Testing Dynamic Behavior</td></tr></table>

<table><tr><td>G2012/04</td><td>M. GAINI - A. LEDUC - A. VICARD<br/>School as a shelter? School leaving-age and the business cycle in France</td></tr><tr><td>G2012/05</td><td>M. GAINI - A. LEDUC - A. VICARD<br/>A scarred generation? French evidence on young people entering into a tough labour market</td></tr><tr><td>G2012/06</td><td>P. AUBERT - M. BACHELET<br/>Disparités de montant de pension et redistribution dans le système de retraite français</td></tr><tr><td>G2012/07</td><td>R. AEBERHARDT - P. GIVORD - C. MARBOT<br/>Spillover Effect of the Minimum Wage in France: An Unconditional Quantile Regression Approach</td></tr><tr><td>G2012/08</td><td>A. EIDELMAN - F. LANGUMIER - A. VICARD<br/>Préférences obligatoires reposant sur les ménages : des canaux redistributifs différents en 1990 et 2010</td></tr><tr><td>G2012/09</td><td>O. BARGAIN - A. VICARD<br/>Le RMI et son successeur le RSA, découragent-lis certains jeunes de travailer ? Une analyse sur les jeunes autour de 25 ans</td></tr><tr><td>G2012/10</td><td>C. MARBOT - D. ROY<br/>Projections du coût de l'APA et des caractéristiques de ses bénéficiaires à Horizon 2040 à l'aide du modèle Destinie</td></tr><tr><td>G2012/11</td><td>A. MAUROUX<br/>Le crédit d'impôt dédié au développement durable : une évaluation économique</td></tr><tr><td>G2012/12</td><td>V. COTTET - S. QUANTIN - V. RÉGNIER<br/>Coût du travail et allégements de charges: une estimation au niveau établissement de 1996 à 2008</td></tr><tr><td>G2012/13</td><td>X. D'HAULTFOEUILLE - P. FÉVRIER -<br/>L. WILNER<br/>Demand Estimation in the Presence of Revenue Management</td></tr><tr><td>G2012/14</td><td>D. BLANCHET - S. LE MINEZ<br/>Joint macro/micro evaluations of accrued-to-date pension liabilities: an application to French reforms</td></tr><tr><td>G2013/01</td><td>T. DEROYON - A. MONTAUT - P.-A. PIONNIER<br/>Utilisation rétrospective de l'enquête Emploi à une fréquence mensuelle: apport d'une modélisation espace-état</td></tr><tr><td>G2013/02/<br/>F1302</td><td>C. TREVIEN<br/>Habiter en HLM: quel avantage monétaire et quel impact sur les conditions de logement?</td></tr><tr><td>G2013/03</td><td>A. POISSONNIER<br/>Temporal disaggregation of stock variables - The Chow-Lin method extended to dynamic models</td></tr><tr><td>G2013/04</td><td>P. GIVORD - C. MARBOT<br/>Does the cost of child care affect female labor market participation? An evaluation of a French reform of childcare subsidies</td></tr><tr><td>G2013/05</td><td>G. LAME - M. LEQUIEN - P.-A. PIONNIER<br/>Interpretation and limits of sustainability tests in public finance</td></tr><tr><td>G2013/06</td><td>C. BELLEGO - V. DORTET-BERNADET<br/>La participation aux poles de compétitivité: quelle incidence sur les dépenses de R&D et l'activité des PME et ETI?</td></tr></table>

<table><tr><td>G2013/07</td><td>P.-Y. CABANNES - A. MONTAUT -<br/>P.-A. PIONNIER<br/>Évaluer la productivité globale des facteurs en France: l'apport d'une mesure de la qualité du capital et du travail</td></tr><tr><td>G2013/08</td><td>R. AEBERHARDT - C. MARBOT<br/>Evolution of Instability in the French Labour Market During the Last Thirty Years</td></tr><tr><td>G2013/09</td><td>J.-B. BERNARD - G. CLÉAUD<br/>Oil price: the nature of the shocks and the impact on the French economy</td></tr><tr><td>G2013/10</td><td>G. LAME<br/>Was there a « Greenspan Conundrum » in the Euro area?</td></tr><tr><td>G2013/11</td><td>P. CHONE - F. EVAIN - L. WILNER - E. YILMAZ<br/>Introducing activity-based payment in the hospital industry: Evidence from French data</td></tr><tr><td>G2013/12</td><td>C. GRISLAIN-LETREMY<br/>Natural Disasters: Exposure and Underinsurance</td></tr><tr><td>G2013/13</td><td>P.-Y. CABANNES - V. COTTET - Y. DUBOIS -<br/>C. LELARGE - M. SICMIC<br/>French Firms in the Face of the 2008/2009 Crisis</td></tr><tr><td>G2013/14</td><td>A. POISSONNIER - D. ROY<br/>Households Satellite Account for France in 2010, Methodological issues on the assessment of domestic production</td></tr><tr><td>G2013/15</td><td>G. CLÉAUD - M. LEMOINE - P.-A. PIONNIER<br/>Which size and evolution of the government expenditure multiplier in France (1980-2010)?</td></tr><tr><td>G2014/01</td><td>M. BACHELET - A. LEDUC - A. MARINO<br/>Les biographies du modèle Destinie II: rebagage et projection</td></tr><tr><td>G2014/02</td><td>B. GARBINTI<br/>L'achat de la résidence principale et la création d'entreprises sont-ils favorisés par les donations et héritages?</td></tr><tr><td>G2014/03</td><td>N. CECI-RENAUD - P. CHARNOZ - M. GAINI<br/>Evolution de la volatilité des revenus salariaux du secteur privé en France depuis 1968</td></tr><tr><td>G2014/04</td><td>P. AUBERT<br/>Modalités d'application des réformes des retraites et prévisibilité du montant de pension</td></tr><tr><td>G2014/05</td><td>C. GRISLAIN-LETREMY - A. KATOSSKY<br/>The Impact of Hazardous Industrial Facilities on Housing Prices: A Comparison of Parametric and Semiparametric Hedonic Price Models</td></tr><tr><td>G2014/06</td><td>J.-M. DAUSSIN-BENICHOU - A. MAUROUX<br/>Turning the heat up: How sensitive are households to fiscal incentives on energy efficiency investments?</td></tr><tr><td>G2014/07</td><td>C. LABONNE - G. LAME<br/>Credit Growth and Capital Requirements: Binding or Not?</td></tr><tr><td>G2014/08</td><td>C. GRISLAIN-LETREMY et C. TREVIEN<br/>The Impact of Housing Subsidies on the Rental Sector: the French Example</td></tr><tr><td>G2014/09</td><td>M. LEQUIEN et A. MONTAUT<br/>Croissance potentielle en France et en zone euro: un tour d'horizon des méthodes d'estimation</td></tr></table>
<table><tbody><tr><td>G2014/10</td><td>B. GARBINTI - P. LAMARCHE</td></tr><tr><td>G2014/11</td><td>D. AUDENAERT - J. BARDAJI - R. LARDEUX - M. ORAND - M. SICRIC</td></tr><tr><td>G2014/12</td><td>F. ARNAUD - J. BOUSSARD - A. POISSONNIER - H.-H. SOUAL</td></tr><tr><td>G2014/13</td><td>H. FRAISSE - F. KRAMARZ - C. PROST</td></tr><tr><td>G2014/14</td><td>P. GIVORD - C. GRISLAIN-LETRÉMY - H. NAEGLE</td></tr><tr><td>G2014/15</td><td>P. AUBERT - S. RABATÉ</td></tr><tr><td>G2015/01</td><td>A. POISSONNIER</td></tr><tr><td>G2015/02</td><td>Y. DUBOIS - A. MARINO</td></tr><tr><td>G2015/03</td><td>T. MAYER - C. TREVIAN</td></tr><tr><td>G2015/04</td><td>S.T. LY - A. RIEGERT</td></tr><tr><td>G2015/05</td><td>M. A. BEN HALIMA - V. HYAFIL-SOLELHAC</td></tr><tr><td>G2015/06</td><td>M. KOUBI - C. REGAART</td></tr><tr><td>G2015/07</td><td>B. CAMPAGNE - V. ALHENC-GELAS - J.-B. BERNARD</td></tr><tr><td>G2015/08</td><td>O. LAFFÉTER - M. PAK</td></tr><tr><td>G2015/09</td><td>J.-M. DAUSSIN-BENICHOU, S. IDMACHICHE, A. LEDUC et E. POUILLIEN</td></tr><tr><td>G2015/10</td><td>P. AUBERT</td></tr><tr><td>G2015/11</td><td>V. DORTET-BERNADET - M. SICRIC</td></tr></tbody></table>

<table><tbody><tr><td>G2015/12</td><td>S. GEORGES-KOT</td></tr><tr><td>G2015/13</td><td>M. POULHÉS</td></tr><tr><td>G2015/14</td><td>J.-B. BERNARD - Q. LAFFÉTER</td></tr><tr><td>G2015/15</td><td>C. GEAY - M. KOUBI - G. DE LAGASNERIE</td></tr><tr><td>G2015/16</td><td>J. BARDAJI - J.-C. BRICONGNE - B. CAMPAGNE - G. GAULIER</td></tr><tr><td>G2015/17</td><td>C. BELLÉGO - R. DE NIJS</td></tr><tr><td>G2015/18</td><td>J.-B. BERNARD - L. BERTHET</td></tr><tr><td>G2015/19</td><td>M. POULHÉS</td></tr><tr><td>G2016/01</td><td>B. GARBINTI - S. GEORGES-KOT</td></tr><tr><td>G2016/02</td><td>P. CHARNOZ - C. LELARGE - C. TREVIAN</td></tr><tr><td>G2016/03</td><td>C. BONNET - B. GARBINTI - A. SOLAZ</td></tr><tr><td>G2016/04</td><td>D. BLANCHET - E. CAROLI - C. PROST - M. ROGER</td></tr><tr><td>G2016/05</td><td>B. CAMPAGNE - A. POISSONNIER</td></tr><tr><td>G2016/06</td><td>B. CAMPAGNE - A. POISSONNIER</td></tr><tr><td>G2016/07</td><td>B. CAMPAGNE - A. POISSONNIER</td></tr><tr><td>G2016/08</td><td>Y. DUBOIS et M. KOUBI</td></tr><tr><td>G2016/09</td><td>A. NAOUAS - M. ORAND - I. SLIMANI HOUTI</td></tr><tr><td>G2016/10</td><td>T. BLANCHET - Y. DUBOIS - A. MARINO - M. ROGER</td></tr><tr><td>G2016/11</td><td>M. PAK - A. POISSONNIER</td></tr><tr><td>G2016/12</td><td>Accounting for technology, trade and final</td></tr></tbody></table>

<table><tbody><tr><td>G2017/01</td><td>D. FOUGÈRE - E. GAUTIER - S. ROUX</td></tr><tr><td>G2017/02</td><td>Y. DUBOIS - M. KOUBI</td></tr><tr><td>G2017/03</td><td>A. CAZENAVE-LACROUTZ - F. GODET</td></tr><tr><td>G2017/04</td><td>J. BARDAJI - B. CAMPAGNE - M.-B. KHDER - Q. LAFFÉTER - O. SIMON (Insee)</td></tr><tr><td>G2017/05</td><td>A. S. DUFERNEZ - C. ELEZAAR - P. LEBLANC - E. MASSON - H. PARTOUCHE (DG-Trésor)</td></tr><tr><td>G2017/06</td><td>Le modèle macroéconométrique Mésange : réestimation et nouveau s</td></tr><tr><td>G2017/07</td><td>J. BOUSSARD - B. CAMPAGNE</td></tr><tr><td>G2017/08</td><td>Fiscal Policy Coordination in a Monetary Union at the Zero-Lower-Bound</td></tr><tr><td>G2017/09</td><td>A. CAZENAVE-LACROUTZ - A. GODZINSKI</td></tr><tr><td>G2017/10</td><td>Effects of the one-day waiting period for sick leave on health-related absences in the French central civil service</td></tr><tr><td>G2017/11</td><td>P. CHARNOZ - M. ORAND</td></tr><tr><td>G2017/12</td><td>Qualification, progrès technique et marchés du travail locaux en France, 1990-2011</td></tr><tr><td>G2017/13</td><td>K. MILIN</td></tr><tr><td>G2017/14</td><td>Modélisation de l'inflation en France par une approche macrosectorielle</td></tr><tr><td>G2017/15</td><td>C.-M. CHEVALIER - R. LARDEUX</td></tr><tr><td>G2017/16</td><td>Homeownership and labor market outcomes: disentangling externality and composition effects</td></tr><tr><td>G2017/17</td><td>P. BEAUMONT</td></tr><tr><td>G2017/18</td><td>Time is Money: Cash-Flow Risk and Export Market Behavior</td></tr><tr><td>G2017/19</td><td>S. ROUX - F. SAVIGNAC</td></tr><tr><td>G2017/20</td><td>SMEs' financing: Divergence across Euro area countries?</td></tr><tr><td>G2017/21</td><td>C.-M. CHEVALIER - A. LUCIANI</td></tr><tr><td>G2017/22</td><td>Computerization, labor productivity and employment: impacts across industries vary with technological level</td></tr><tr><td>G2017/23</td><td>R. MONIN - M. SUAREZ CASTILLO</td></tr><tr><td>G2017/24</td><td>"L'effet du CICE sur les prix : une double analyse sur donnés sectorielles et individuelles</td></tr><tr><td>G2017/25</td><td>R. LARDEUX</td></tr><tr><td>G2017/26</td><td>Who Understands The French Income Tax?</td></tr><tr><td>G2017/27</td><td>Bunching Where Tax Liabilities Start</td></tr></tbody></table>

<table><tbody><tr><td>G2018/05</td><td>C.-M. CHEVALIER</td></tr><tr><td>G2018/06</td><td>R. S.-H. LEE - M. PAK</td></tr><tr><td>G2018/07</td><td>C.-M. CHEVALIER</td></tr><tr><td>G2018/08</td><td>Consumption inequality in France between 1985 and 2011</td></tr><tr><td>G2018/09</td><td>A. BAUER - B. GARBINTI - S. GEORGES-KOT</td></tr><tr><td>G2018/10</td><td>A. BEAUMONT - A. LUCIANI</td></tr><tr><td>G2018/11</td><td>Prime à l'embauche dans les PME : évaluation à partir des déclarations d'embauche</td></tr><tr><td>G2018/12</td><td>A. CAZENAVE-LACROUTZ - F. GODET - V. LIN</td></tr><tr><td>G2018/13</td><td>L'introduction d'un gradient social dans la mortalité au sein du modèle Destinie 2</td></tr><tr><td>G2018/14</td><td>M. ANDRÉ - A.-L. BIOTTEAU</td></tr><tr><td>G2018/15</td><td>Effets de moyen terme d'une hausse de TVA sur le niveau de vie et les inégalités: une approche par microsimulation</td></tr><tr><td>G2018/16</td><td>A. BOURGEOIS - A. BRIAND</td></tr><tr><td>G2018/17</td><td>Le modèle Avionique : la modélisation Input/Output des comptes nationaux</td></tr><tr><td>G2018/18</td><td>A. GODZINSKI - M. SUAREZ CASTILLO</td></tr><tr><td>G2018/19</td><td>Short-term health effects of public transport disruptions: air pollution and viral spread channels</td></tr><tr><td>G2018/20</td><td>L. AEBERHARDT - F. HATIER - M. LECLAIR - B. PENTINAT - J.-D. ZAFAR</td></tr><tr><td>G2018/21</td><td>"L'économie numérique fausse-t-elle le partage volume-prix du PIB ?</td></tr><tr><td>G2018/22</td><td>A. CAZENAVE-LACROUTZ - E. YILMAZ</td></tr><tr><td>G2018/23</td><td>Dans quelle mesure les incitations tarifaires et la procédure de mise sous accord préalable ont-elles contribué au développement de la chirurgie ambulatoire ?</td></tr><tr><td>G2018/24</td><td>J.-P. CLING - S. EGIBAL-TEHERANI - M. ORZONI - C. PLATEAU</td></tr><tr><td>G2018/25</td><td>The Differences between EU Countries for Sustainable Development Indicators: It is (mainly) the Economy?</td></tr><tr><td>G2018/26</td><td>P. CHONÉ - L. WILNER</td></tr><tr><td>G2018/27</td><td>Competition on Unobserved Attributes: The Case of the Hospital Industry</td></tr></tbody></table>
<table><tr><td>G2019/08</td><td>P. PORA – L. WILNER<br/>Child Penalties and Financial Incentives;<br/>Exploiting Variation along the Wage<br/>Distribution</td></tr><tr><td>G2019/09</td><td>E. GAUTIER – S. ROUX – M. SUAREZ<br/>CASTILLO<br/>Do Minimum Wages make Wages more<br/>Rigid ? Evidence from French Micro Data</td></tr><tr><td>G2019/10</td><td>M. ANDRÉ – A. SIREYJOL<br/>Imposition des couples et des familles :<br/>effets budgétaires et redistributifs de l'impôt<br/>sur le revenu</td></tr><tr><td>G2019/11</td><td>K. MOHKAM – O. SIMON<br/>L'entrepreinte matière de l'économie<br/>française : une analyse par matière et<br/>catégorie de produits</td></tr><tr><td>G2019/12</td><td>S. BUNEL – B. HADJIBEYLI<br/>Évaluation du crédit d'impôt innovation</td></tr><tr><td>G2019/13</td><td>C. BONNET – F. GODET – A. SOLAZ<br/>Gendered economic determinants of couple<br/>formation over 50 in France</td></tr><tr><td>G2019/14</td><td>P. GIVORD – M. SUAREZ CASTILLO<br/>Excellence for all? Heterogeneity in high<br/>schools' value-added</td></tr><tr><td>G2019/15</td><td>G. CETTE – L. KOEHL – T. PHILIPPON<br/>Labor Share in Some Advanced Countries</td></tr><tr><td>G2020/01</td><td>J. SILHOL – B. VENTELOU<br/>Les zones d'intervention prioritaire reflétent-<br/>elles des écarts de pratiques des médecins<br/>généralistes ?</td></tr><tr><td>G2020/02</td><td>B. BOUCHTENIK – R. LARDEUX<br/>The Take-Up of Unemployment Benefit<br/>Extensions</td></tr><tr><td>G2020/03</td><td>J-M. GERMAIN<br/>A Welfare Based Estimate of "Real Feel<br/>GDP" for Europe and the USA</td></tr><tr><td>G2020/04</td><td>J. BOUSSARD – R. LEE<br/>Competition, Profit Share and Concentration</td></tr><tr><td>G2020/05</td><td>P. PORA<br/>Keep Working and Spend Less?<br/>Collective Childcare and Parental Earnings<br/>in France</td></tr><tr><td>G2020/06</td><td>R. MONIN – M. SUAREZ CASTILLO<br/>Product Switching, market power and<br/>distance to core competency</td></tr><tr><td>G2020/07</td><td>L. WILNER<br/>How do citizens perceive centralization<br/>reforms? Evidence from the merger of<br/>French regions</td></tr><tr><td>G2020/08</td><td>L. WILNER<br/>The persistence of subjective well-being:<br/>permanent happiness, transitory misery?</td></tr></table>

<table><tr><td>G2020/09</td><td>J-M. GERMAIN – T. LELLOUCH<br/>Comptabilité économique de la soutenabilité<br/>climatique</td></tr><tr><td>G2020/10</td><td>A. BAUER – M. ROTEMBERG<br/>Tax avoidance in French Firms:<br/>Evidence from the Introduction of a Tax<br/>Notch</td></tr><tr><td>G2020/11</td><td>P. AGHION – A. BERGEAUD<br/>M. LEQUIEN – M. J. MELITZ<br/>The Heterogeneous Impact of Market Size<br/>on Innovation: Evidence from French Firm-<br/>Level Exports</td></tr><tr><td>G2020/12</td><td>L. GALIANA – B. SAKAROVITCH<br/>F. SÉMÉCURBE – Z. SMOREDA<br/>Residential segregation, daytime<br/>segregation and spatial frictions : an<br/>analysis</td></tr><tr><td>G2020/13</td><td>A. BAUER – J. BOUSSARD<br/>Market Power and Labor Share</td></tr><tr><td>G2020/14</td><td>D. LASHKARI – A. BAUER – J. BOUSSARD<br/>Information Technology and Returns to<br/>Scale</td></tr></table>