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Melitz (2003) develops a theory that predicts a) which plants will export and b) that exporting plants will increase their share of the industry’s overall production. Melitz finds that only the plants of higher productivity levels are able to compete as exporters. Further, Melitz notes that the plants with the highest productivity levels expand their market share. A comparison of productivity levels between plants of differing export statuses can be used to test the first prediction. Likewise, the market share of exporters can be contrasted with that of non-exporters. However, neither of the empirical tests provides an explanation of the mechanism through which this growth might take place. The remainder of this section devel- ops the estimation strategy that will be used to explore the relationship between investment and exports. More specifically, the methodology seeks to address the role that exporting status plays on a plant’s investment decision. Plant i’s time t investment is assumed to be determined by an investment demand function, which is estimated as:

iit=c0+c1kit−1+c2ωit−1+c3xit+εit, (4.23)

where iit represents the plant’s investment and xit is the plant’s exports. The choice of regressors in (4.23) warrants additional discussion. The variables can be directly related to the plant’s first order condition for investment defined in (4.4). A plant chooses its level of investment to obtain its optimal level of capital given its level of capital in the previous period. The prior level of capital enters the first order condition for investment (4.4) through ΠK, which is a function of the plant’s time t capital,Kt=Kt−1(1−δ) +It. Using a similar Markov process for productivity to that described above, Ericson and Pakes (1995) show that investment is increasing with productivity. The LP estimation method assumes that the current period’s productivity is unknown during the investment process. However, LP also note that productivity follows the Markov process defined in (4.12) and a plant is aware of its

past levels of productivity, when forming its expectation of productivity in the next period. Accordingly, lagged productivity, ωit−1, enters (4.23), which is expected to have a positive

coefficient as predicted by the comparative static in (4.7). The use of lagged productivity makes use of the timing assumption utilized in the estimation of the production function, which supposes that the investment decision is made before the current period’s productivity is known.12

The final term included in (4.23) is the plant’s level of exports.13 The theory in the last section predicts that both investment and exports increase as the plant gains experience in exporting. The reduced export cost creates an incentive for the plant to expand to meet its overseas demand. Under such a premise, investment should be increasing with exports. Such an expansion of the plant’s capital stock and output would support the notion that export-led growth hypothesis occurs at the establishment level.

As noted earlier, many plants in the sample do not invest every year, which results in a censoring of investment that must be included in the estimation process. Thus, the estimation of the investment equation takes the form of the typical Tobit:

i∗_it=c0+c1kit−1+c2ωit−1+c3xit+εit, (4.24) where iit      i∗_it if i∗_it>0 0 otherwise.

The estimation of (4.24) as a Tobit addresses the issue of the censored data, but fails to account for the simultaneity of exports and investment. If investment and exports are simultaneously determined as in the theoretical model presented in the last section, then the failure to address this issue would result in an upward-biased estimate ofc3. Such a bias would

overemphasize the influence exports on investment. Therefore, the instrumental variable

12_{The use of productivity instead of lagged productivity yields similar results. Lagged productivity is used}

in the results presented in this paper to provide consistency in the LP timing assumptions.

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A measure of the cost of capital goods, such as the real interest rate should also be included in the first order condition for investment. However, the coefficient on the real interest rate is positive and insignificant.

Tobit similar to Newey (1987) is used in the estimation process, which applies Amemiya’s (1978) generalized least squares (AGLS). The reduced-form parameter estimates are obtained from the export equation. The estimation begins by treating xit as linear function of the instruments,etand gdpwt , and the other exogenous regressors in (4.24):

xit=a0+a1ωit−1+a2kit−1+a3et+a4gdpwt +a5xit−1+εit. (4.25)

Next, the coefficients on the exogenous variables of the investment equation are then estimated as a Tobit using the predicted value of exports, ˆxit, obtained from a least squares estimate of (4.25):14 i∗_it=c0+c1kit−1+c2ωit−1+c3xit+εit, (4.26) where iit=      i∗_it if i∗_it >0 0 otherwise.

The resulting estimation not only seeks to address the simultaneity issue, but it also closely follows the plant’s decision process. A plant’s expectation of exports in the current period would be determined by foreign demand, relative prices, and the plant’s prior levels of capital and exports. It is this expectation of exports that influences the plant’s investment decision, which is a decision that occurs before the exports are produced.

This section has described the estimation strategy that will be employed to examine the relationship between exports and investment, while also addressing the simultaneity issue between exports and investment. The next subsection presents the results of the previously described estimations. The influences on plant-level exports are also examined.

4.5

Empirical Results

This section uses the methodology discussed to the previous section to provide an analysis of investment and export behavior of plants during the period 1990-1996. The section begins

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with a comparison of productivity measures across exporters and non-exporters. Additional influences on the plant-level export decision are then examined. The remainder of the section concentrates on the plant-level relationship between export status and investment.