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Spillover from FDI and

market structure

Reading Group in Int.l Economics

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Spillovers from MNEs: a long debate

Early empirical studies: OLS

• Caves (1974), Globerman (1979), Blomstrom and Persson (1983) and Blomstrom (1986) => there are positive productivity spillovers from FDI to domestic firms

Second generation studies: panel data and the endogeneity problem

• Aitken and Harrison (1999) => using panel data on Venezuelan plants and controlling for for potential endogeneity, they find no significant intra-industry spillovers from foreign on domestic firms.

• Haddad and Harrison (1993) on Morocco, Djankov and Hoekman (2000) on the Czech Republic, Konings (2001) on Bulgaria, Poland and Romania: either fail to find a significant positive effect or even detect a negative spillovers

• Slightly different evidence for developed countries: some studies have found evidence of positive intra-industry spillovers (e.g., Haskel, Pereira and Slaughter, 2002, using UK plant level data)

• As a result, Gorg and Greenaway (2004) in their survey point out the inconclusive evidence emerging from several empirical contributions on the issue.

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Spillovers from MNEs: where we are today

Third generation studies: panel data & endogeneity + controlling simultaneity and selection bias

• Following the seminal works of Olley and Pakes (1996) and Levinsohn and Petrin (2003), the last generation of papers, in addition to the endogeneity problem, successfully addresses the selection bias that might arise from the non-random data availability of firms (properly exploiting the unbalanced panel nature of the datasets) and the simultaneity bias induced by productivity shocks correlated with firm-level input usage

Debate on the nature of spillovers in the most recent “third generation” studies

• Smarzynska-Javorcik (2004), working on Lithuanian firm-specific data, has detected significant positive spillovers arising trough backward linkages, i.e. generated through contacts between multinational affiliates and local input suppliers. She finds instead no clear evidence in favour of neither intra-industry (horizontal) spillovers, nor forward linkages.

• Similar results have been obtained by Blalock and Gertler (2004) on a sample of Indonesian firms.

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Beata Smarzynska – Javorcik

American Economic Review, 2004

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Introduction

Relevance of the problem => examples and quotations

In 1991, Motorola was paid 50.75 million pounds to locate a mobile -phone factory employing 3,000 people in Scotland

As Dani Rodrik (1999) remarked, “today’s policy literature is filled with extravagant claims about positive spillovers from FDI but the evidence is sobering.”

Literature review => see above

Intuition => “It is possible, though, that researchers have been looking for FDI spillovers in the wrong place” => backward linkages + theoretical justification [Rodriguez-Clare (1996), Markusen and Venables (1999), Saggi (2002)]

Purpose of the study:

1) examine whether the productivity of domestic firms is correlated with the presence of multinationals in downstream sectors

2) improve over the existing literature by taking into account econometric problems that may have biased the results of earlier work => Olley and Pakes (1996) correction + clustering of standard errors

3) go beyond the existing literature by shedding some light on determinants of spillovers => export-orientation of multinationals in downstream sectors and the extent of foreign ownership in affiliates

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Introduction

Dataset to be used: data from the annual enterprise survey conducted by the Lithuanian Statistical Office survey coverage: 85 percent of output in each sector

nature of the data and period: unbalanced panel spanning over the period 1996-2000

choice of the dataset: transition economy, “as the endowment of skilled labor enjoyed by transition countries makes them a particularly likely place where productivity spillovers could manifest themselves” (….)

Summary of results:

1) empirical evidence consistent with the existence of positive spillovers from FDI taking place through backward linkages (a 10% increase in the foreign presence in downstream sectors is associated with a 0.38 % rise in output of each firm in the supplying industry), but no indication of spillovers occurring through horizontal channels

2) correlations are not local in nature, that is, they are not restricted exclusively to foreign firms operating in the same region of the country but also to other regions

3) productivity effect is larger when the multinationals in the sourcing sector are oriented towards supplying the domestic market rather than focusing mainly on exporting (Markusen and Venables, 1999)

4) no statistically significant difference between the productivity effects associated with partially- and fully-owned foreign projects

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Vertical vs. horizontal spillovers

(i) direct knowledge transfer from foreign customers to local firms;

(ii) higher requirements regarding product quality and on-time delivery introduced by multinationals, which provide incentive to domestic firms to upgrade their production management or technology;

(iii) indirect knowledge transfer through movement of labor;

(iv) increased demand for intermediate products due to multinational entry, which allows local suppliers to reap the benefits of scale economies;

(v) competition effect - multinationals acquiring domestic firms may choose to source intermediates abroad thus breaking existing supplier-customer relationships and increasing competition in the intermediate products

See Castellani and Zanfei (2006) for a comprehensive survey

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Aggregate FDI data

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Sample description for a given year (2000)

Sample’s dimension ranges from 1,921 to 2,712 firms over the considered period; NACE D only (- 16 and 23)

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Initial specificationA log-linearized Cobb-Douglas production function with K, L, and Material inputs, integrated with foreign share (FS), measures of horizontal and backward presence, and control dummies

Yit stands for firm i’s real output at time t, which is calculated by adjusting the reported sales for changes in inventories of finished goods and deflating the resulting value by the Producer Price Index for the appropriate two-digit NACE sector

Kit, capital, is defined as the value of fixed assets at the beginning of the year, deflated by the average of the deflators for four NACE sectors: machinery and equipment; office, accounting and computing machinery; electrical machinery and apparatus; motor vehicles, trailer and semi-trailers; and other transport equipment

Lit, employment, is measured by the number of workers

Mit, material inputs, are equal to the value of material inputs adjusted for changes in material inventories, deflated by a material inputs deflator, calculated for each sector based on the two-digit input-output matrix + deflators for the relevant two-digit NACE sectors

Huge debate on the technique for deflationing: Klette and Griliches (1996); Tybout et al. (2005); De Loecker (2005, JMP)

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Measurement of horizontal and backward linkages

defined as foreign equity participation FS averaged over all firms in the sector, weighted by each

firm’s share in sectoral output at time t: Yijt/Yjt

Alternative definitions exist in the literature (do not consider FS, just the share of output or

employment of firms considered as foreign)

where jk is the proportion of sector j output supplied to sector k taken from the 1996 Input /

Output matrix at the two-digit NACE level. The formula excludes inputs supplied within the

sector, captured by the Horizontal variable

This is the current standard in the literature (for forward linkages as well: proportion of sector j

output purchased by sector k)

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Refined specification

Econometric problems with the previous specification:

• Unobserved fixed characteristics might be correlated with the presence of foreign firms (FS) and thus generate an endogeneity bias: first differencing every variable

• Include in any case time-, region and industry fixed effects to account for other unobserved characteristics not wiped-out by first differencing (e.g. regional incentives varying over time)

Problems with the economic interpretation of ? Alternative solutions ?

• Self selection of foreign firms into “best” domestic companies whose characteristics are unobserved by the econometrician (“cherry picking” attitude) => spurious correlation between Y it

and FSit: run the estimates on a sub-sample of domestic firms only, or pre-filter the data through an

Heckman-type two-step selection model (used in this case as a robustness check)

• Regressions performed on micro i units including aggregated j-variables lead to downward bias in the estimated errors => spurious finding of statistical significance for the aggregate variable of interest: cluster standard errors for all observations for the same industry and year (robust estimation)

• Further (huge) econometric problem: simultaneity bias when estimating TFP

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OP (1996) or LP (2003) ?• Both methods widely used in the literature

• The data requirement of both methods is quite significant, since estimates should be carried out using industry-specific samples and thus you need enough obs. in each industry to allow for a consistent identification of parameters.

[imposing constant elasticities across industries yields “average” => underestimation of TFP in industries with DRS, and overestimation in industries with IRS]

OP needs to assume positive investments to impose the invertibility condition on As such, all firms with negative or zero investments have to be dropped out from the sample, potentially generating problems with the DF in the identification of the parameters. However, the monotonicity conditions needed to invert the investment function are pretty general, not depending on the degree of competition on the output market, but only requiring the marginal product of capital to be increasing in productivity.

• LP instead need firms to operate in a competitive environment and take output and input prices as given in order for the intermediate input to be monotonic increasing in productivity, thus being able to invert the productivity shocks and proceed as in Olley and Pakes (1996). They provide a series of “checks” to be performed to this extent.

• In general, however, models of imperfect competition on the output market do not satisfy those assumptions. However, Melitz (2001) shows that LP can be used provided that more productive firms do not set disproportionately higher markups than the less productive firms.

[another rationale for splitting estimates across industries and firms’ types. See De Loecker (2005) for a nice discussion of these and related problems + possible solutions]

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Spillovers from MNEs: where we are today

Third generation studies: panel data & endogeneity + controlling simultaneity and selection bias

• Following the seminal works of Olley and Pakes (1996) and Levinsohn and Petrin (2003), the last generation of papers, in addition to the endogeneity problem, successfully addresses the selection bias that might arise from the entry and exit of firms given the unbalanced panel nature of the datasets, and the simultaneity bias induced by productivity shocks correlated with firm-level input usage

Debate on the nature of spillovers in the most recent “third generation” studies

• Smarzynska-Javorcik (2004), working on Lithuanian firm-specific data, has detected significant positive spillovers arising trough backward linkages, i.e. generated through contacts between multinational affiliates and local input suppliers. She finds instead no clear evidence in favour of neither intra-industry spillovers, nor forward linkages.

• Similar results have been obtained by Blalock and Gertler (2004) on a sample of Indonesian firms.

• More recent works by Criscuolo and Martin (2004), Smarzynska-Javorcik and Spatareanu (2004 & 2005); Altomonte and Pennings (2008) and Amiti and Konings (2007) explore through these methodologies various other hypotheses on the nature of spillovers (respectively: perfect vs. imperfect competitive markets, MNEs ownership structure and/or nationality effect, persistency over time, impact of trade liberalization)

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Smarzynska (2004) summarizes the following factors as affecting the existence of “vertical” spillovers (backward linkages)

(i) direct knowledge transfer from foreign customers to local firms;

(ii) higher requirements regarding product quality and on-time delivery introduced by multinationals, which provide incentive to domestic firms to upgrade their production management or technology;

(iii) indirect knowledge transfer through movement of labor;

(iv) increased demand for intermediate products due to multinational entry, which allows local suppliers to reap the benefits of scale economies;

But the same effects can justify the emergence of horizontal spillovers….

Alfaro and Rodriguez-Clare (2004): if multinationals generate positive externalities to (upstream) domestic suppliers, the increase in the quality of inputs they produce should also lead, sooner or later, to increases in the TFP of downstream domestic firms => even indirectly, one should find evidence of horizontal spillovers

Spillovers from MNEs: an identification problem?

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Traditional specification for detecting spillovers from an augmented production function framework:

ln(TFPit) = + FDIi, t+ Xit + it

where the TFP of each domestic firm’s i is regressed against an indicator of MNE’s “presence” over an homogeneous group of domestic firms, and some individual firm’s characteristics X (eventually in first-differences to wipe-out unobserved heterogeneity)

Interpretation of the estimated : average of

1)cross-sectional variation (impact of MNEs across individual firms in each period)

2)time-variation (impact of MNEs on each firm across time)

Spillovers and market structure

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Examples of 1) cross-sectional variation from MNEs’ entry: - technological externality: reduction in marginal costs for domestic firms and increase in TFP (horizontal spillover) - negative competition effect:

a) Product market: due to the reduction in a domestic firm’s output, TFP tends to decrease after the entry of a competitor (economies of scale, slow adjustment in inputs, partial usage of capital…)b) Labor market: MNEs attract higher-skilled workers due to higher wages

Examples of 2) time-variation from MNEs’ entry:- convergence to the frontier of domestic firms’ TFP (Griffith et al., 2002)- possible increase in the crowding-out of domestic firms as more MNEs enter

Spillover and market structure

The combination of 1+2 might yield ambiguous (and ultimately insignificant) results

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“Marginal” spillovers: an example• Assume:

1) cross-sectional effect: horizontal spillovers + negative competition

2) Time-variation effect: convergence to the frontier

• If one tries to measure both effects with only one coefficient averaged over time, the overall message is likely not significant and not very informative

• Rather, we should econometrically test for the existence of a “threshold”

MNEs’ entry (t)

TFP dom firms

Positive horizontal spillover (convergence)

Negative competition effect (constant)

Net effect: there might exist a threshold FDI* after which spillovers become negative

FDI*

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Model design – 1

“Third generation” methodology:

• endogeneity bias: industry, regional and time fixed effects z , j , t + first differencing

TFP measure to wipe-out firm-specific fixed effects + lagging the MNE’s presence

• simultaneity bias: semi-parametric firm-specific TFP estimates of domestic firms (Levinsohn-Petrin)

• selection bias: check robustness of TFP measures on balanced vs. unbalanced sample

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Model design – 2

As before plus:• Gets rid of the assumption on the HP indicator that an equiproportional increase in MNEs presence

and total employment (thus yielding a constant share) will have no effect on domestic firms

productivity => downward bias in (Castellani and Zanfei, 2003)

• Tests for marginal spillovers (“instantaneous learning” case):

• coeff. of Dzjt-1 (dummy = 1 if MNEs entry at time t-1) positive and significant

• coeff. of Dzjt-1CumFDIzjt-1 negative and significant

• positive spillover if + CumFDIzjt-1 > 0 and negative if < 0;

• critical threshold: if CumFDI* = - / + CumFDIzjt-1= 0

• test statistic for marginal spillovers: if - /significantly different from zero, there exists a

threshold value of FDI below which aggregate spillovers are positive. Spillovers then become

negative as soon as MNEs’ entry proceeds

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Model design – 3

As before plus:• omitted price variable bias: balanced panel of average (over individual firms) industry and regional

TFP changes, since the latter might also be responsible for a downward bias in

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The dataset

• Validation => proxy regional aggregate output through the sum of the available observations of firm-specific turnover (for domestic and MNEs), deflated using 48 industry-specific price indices homogeneous in terms of industry characteristics (Davies and Lyons or Pavitt classifications)

• Correlations with official GDP regional data: 0.83 and significant

• Data on all Romanian firms are recorded by the Romanian Chamber of Commerce and Industry and made commercially available by AMADEUS in different versions (small, intermediate or entire sample). We employ here the 2004 intermediate edition of AMADEUS for Romania, comprising originally 30,148 firms.

• For a smaller sample yearly balance sheet data are available on: Tangible and Intangible Fixed Assets; Total Assets; Number of Employees; Material Costs; Turnover; Ownership

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The dataset: industry distribution of multinational firms

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Levinsohn-Petrin vs. OLS productivity estimates

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Levinsohn-Petrin vs. OP productivity estimates: TFP

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Refined model design

Testing hypotheses (“instantaneous learning” case + industry-specific threshold):

• Dzjt-1 (dummy = 1 if MNEs entry at time t-1) positive and significant

• [Dzjt-1CumFDIzjt-1 / MESz] negative and significant

• critical (industry-specific) threshold: CumFDIz* = - /MESz - / test

statistics)

• Aitken and Harrison (1999) distinguish between large and small domestic firms: large firms are more likely to possess a sufficient level of absorptive capacity to benefit from the presence of FDI

our threshold should depend on MESi, the minimum efficient scale of sector i:

industries characterised by larger firms (i.e. a higher MES) should exhibit a higher critical threshold level of FDI after which their spillover becomes negative

ln(TFPzjt) = Dzjt-1 + Dzjt-1CumFDIzjt-1 / MESz] + Dzjt-1 / MESz] + z + j + t + ijt

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Results:

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Results:

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Summary of results

1. In the case of Romania, a developing economy, there exists a (industry-specific) threshold of MNEs driving the results of aggregate spillovers.

2. As a result, traditional interpretations of the “spillover” coefficient in a standard panel design might be misleading

3. In particular, special attention should be devoted to the design of policies for attracting FDI:

a. focus on industries where the marginal impact of foreign entry is high since in industries with lower FDI thresholds any new FDI entering the market might lead to vanishing spillovers for domestic firms;

b. alternatively, work to increase the threshold (e.g. absorptive capacity)

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Future lines of research

Econometric techniques for measuring spillovers

A “fourth generation” study of spillover might soon emerge using TFP estimates which also control for the omitted price variable bias (Klette and Griliches, 1995; De Loecker, 2005) and the product choice bias (Bernard, Redding and Schott, 2005; Bernarnd, Jensen and Schott, 2006)

Further insights in the debate on the nature of spillovers

The nature of the competition effect remains unclear: what drives the reduction in domestic firms’ TFP as MNEs enter the host market?

(a) a slow adjustment in inputs due to adjustment costs => but this adjustment should be progressively incorporated over time by local firms

(b) lower economies of scale accruing to domestic firms given the compression of market sizes => but the latter holds only for IRS industries, a restriction not imposed in our sample

(c) ‘strategic’ technology transfers of MNEs => if MNE transfers technology to domestic suppliers (vertical spillovers), the higher the number of MNEs, the higher the risk of indirect spillovers to downstream domestic competitors: hence MNEs will start to strategically reduce technology transfers (Blalock and Gertler, 2004).

(d) Analogously, the technology transfer to multinational affiliates will be progressively reduced as foreign competitors enter the market, since the incumbent MNEs face the risk of dissipation of their know-how to rivals (Belderbos et al., 2005)