fool´s gold: the case of multinationals in venezuela

Fool´s Gold: The case of multinationals in Venezuela

January, 2017

Miguel Ángel SantosInstituto de Estudios Superiores en Administración (IESA)Center for International Development, Harvard University

[email protected]

Dany BaharInter-‐American Development Bank

Brookings Institute

Carlos MolinaInstituto de Estudios Superiores en Administración (IESA)

Jan 11, 2010

JAN 11, 2010

JAN 12, 2010

Feb 11, 2013

Feb 14, 2013

Jul 8, 2014

FEB 2, 2015

Feb 11, 2015

Feb 13, 2015

APR 26, 2016

Venezuela represents 0.42% of the world´s GDP!

01/13/2017 12Fool´s gold: The case of multinationals in Venezuela

Venezuela´s*Share*of*World´s*Gross*Domestic*Product

13

• The paper within the context of the literature

• Empirical analysis: Are the negative impacts reported real?

• Robustness checks: Peer groups

• What happened?

• Conclusions

1301/13/2017 Fool´s gold: The case of multinationals in Venezuela

The paper within the context of the literature: What have others found?

• Ang and Ghallab (1976):

• A currency devaluation in the country of a foreign subsidiary could lead to a “balance sheet effect”: net value of assets of the subsidiary in foreign currency will be lower after a devaluation (one time events – straightforward to calculate)

• Yet, there is also an “income statement effect”: a decrease in the expected value of the future earnings (in local currency) of the subsidiary: Recurring impacts on financial statements and take time to understand and estimate

• Glen (2002) studies 24 emerging markets using monthly stock returns, and finds significant negative returns in the months before, not after, the devaluation

• Patro, Wald and Wu (2014) using data from stock markets in 27 countries and about 85 announcements of devaluations, find that devaluations were anticipated by the local stock markets, with significant negative abnormal returns occurring even one year prior to the announcement of devaluations.


15




• What happened?

• Conclusions


Event study: Are there negative abnormal returns on stock prices of multinationals (MNCs) in Venezuela around the dates of these devaluations?

• We estimate a market model to measure expected return of the MNC stocks during the event window. As in Mackinlay (1997), we estimate [1], using least squares:

R"# = α" + β"R(# + ε"# [1]

• Event window: (-‐280, -‐30)• Cox and Peterson (1994): 100 days• Carow and Kane (2002): 200 days• Mackinlay (1997) suggests 250 days for the estimation window [-‐280,-‐30]

We then estimate the abnormal return (AR) as:

AR+ "# = R"# − α-" − β."R(# [2]

AR+ "# =


Actual Return -‐ Expected return

Data

• We searched the ORBIS database looking for:• Companies trading at the New York Stock Exchange (NYSE), NASDAQ Capital Market,

or NASDAQ National Market• Companies declaring having a subsidiary in Venezuela, own in more than 25%• Companies having daily stock return data reported for 2010-‐2014

• Results of the query:• 122 multinational companies (2-‐digit NAICS)

• NAICS 33: 37 Primary Metal, Fabricated Metal, and Machinery Manufacturing • NAICS 32: 36 Paper, Chemicals, Plastics and Non-‐metallic manufacturing• NAICS 51: 8 Information Technology• NAICS 52: 7 Finance and Insurance• NAICS 54: 7 Business, Professional, Scientific, and Technical Services• NAICS 31: 6 Food, Beverages and Tobacco• NAICS 42: 6 Wholesale trade • NAICS 56: 5 Administrative Support, Backoffice / Waste Management• NAICS 48: 4 Transport and Warehousing• Other (6)

• 29 registered in CADIVI


Distribution of the 122 MNCs by 2-‐digit NAICS code


Primary,(Fabricated(Metal,(Machinery

Paper(and(Chemicals

Information(Technology

Finance(and(Insurance

Professional,( Scientific,(Technical(Services

Food,( Beverage(and(Tobacco

Wholesale( Trade

Administrative(Support(/(Waste(Management

Transportation(and(Warehousing

Mining,(Quarrying,(Oil(and(Gas

Utilities

Distribution of the 122 MNCs by 3-‐digit NAICS code: Primary and Fabricated Metal, Machinery Manufacturing



Paper(and(Chemicals





Wholesale( Trade




Utilities

Machinery

Fabricated.Metal

Computer./.Electronics

Transportation

Miscellaneous

Electrical.Equipment.and.Components

Primary.Metal

Distribution of the 122 MNCs by 3-‐digit NAICS code: Paper and Chemicals


Paper

Printing*and*Related

Chemical

Plastics*and*Rubber

Nonmetallic*Mineral


Paper(and(Chemicals





Wholesale( Trade




Utilities

Five events: Five devaluations occurring within January 2010 and March 2014

21

Event Date Details

1 Jan 8th, 2010 Dual exchange rate system implemented:From 2.15 VEF/US$ to 2.50 VEF/US$ and 4.30 VEF/US$

2 December 30th, 2010 Exchange rate unified to 4.30 VEF/US$

3 February 8th, 2013 Devaluation from 4.30 to 6.30 VEF/US$

4 January 23rd, 2014 Creation of SICAD I starting at 11.30 VEF/US$

5 March 10th, 2014 Creation of SICAD II starting at 51.86 VEF/US$


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

-0.006705** -0.005578 -0.009918** -0.010467** -0.009577* -0.013702** -0.013137** -0.014786*** -0.011713** -0.013871**0.002886 0.003608 0.003893 0.0048212 0.004973 0.005419 0.005627 0.005576 0.005672 0.005959

0.022 0.125 0.012 0.032 0.056 0.013 0.021 0.009 0.041 0.021-0.001889 -0.007080*** -0.01359*** -0.012777*** -0.016001*** -0.014068*** -0.012111*** -0.008407* -0.004515 -0.0038970.001208 0.001621 0.002201 0.002822 0.003845 0.004124 0.004171 0.004757 0.005191 0.005283

0.120 0.000 0.000 0.000 0.000 0.001 0.004 0.079 0.386 0.462-0.003433** -0.002839 -0.001386 0.004211 0.002915 0.006915 0.004438 -0.001558 -0.002671 -0.003207

0.001367 0.002557 0.003055 0.003541 0.003807 0.004499 0.004724 0.005176 0.00567 0.0057070.013 0.269 0.651 0.237 0.445 0.127 0.349 0.764 0.638 0.575

-0.007928*** -0.009218*** -0.008240*** -0.008107* -0.011500** -0.007191 -0.00897 -0.008084 -0.008139 -0.0093240.002248 0.002577 0.002845 0.004131 0.005222 0.005713 0.005955 0.006322 0.006724 0.007343

0.001 0.000 0.004 0.052 0.029 0.210 0.134 0.203 0.228 0.206-0.004194* -0.00387 -0.006357** -0.005308* -0.007951** -0.007162 -0.008087* -0.006438 -0.001011 -0.003141

0.002338 0.002557 0.002871 0.003139 0.003997 0.004524 0.004718 0.005213 0.005361 0.0052220.075 0.132 0.028 0.093 0.049 0.116 0.089 0.219 0.851 0.549

Coefficients *++p<0.10+Robust+Standard+Errors **+p<0.05P;values ***+p<0.01

Event Window

1

2

3

4

5

Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10]


Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10] – All sample


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

-0.006705** -0.005578 -0.009918** -0.010467** -0.009577* -0.013702** -0.013137** -0.014786*** -0.011713** -0.013871**0.002886 0.003608 0.003893 0.0048212 0.004973 0.005419 0.005627 0.005576 0.005672 0.005959

0.022 0.125 0.012 0.032 0.056 0.013 0.021 0.009 0.041 0.021-0.001889 -0.007080*** -0.01359*** -0.012777*** -0.016001*** -0.014068*** -0.012111*** -0.008407* -0.004515 -0.0038970.001208 0.001621 0.002201 0.002822 0.003845 0.004124 0.004171 0.004757 0.005191 0.005283

0.120 0.000 0.000 0.000 0.000 0.001 0.004 0.079 0.386 0.462-0.003433** -0.002839 -0.001386 0.004211 0.002915 0.006915 0.004438 -0.001558 -0.002671 -0.003207

0.001367 0.002557 0.003055 0.003541 0.003807 0.004499 0.004724 0.005176 0.00567 0.0057070.013 0.269 0.651 0.237 0.445 0.127 0.349 0.764 0.638 0.575

-0.007928*** -0.009218*** -0.008240*** -0.008107* -0.011500** -0.007191 -0.00897 -0.008084 -0.008139 -0.0093240.002248 0.002577 0.002845 0.004131 0.005222 0.005713 0.005955 0.006322 0.006724 0.007343

0.001 0.000 0.004 0.052 0.029 0.210 0.134 0.203 0.228 0.206-0.004194* -0.00387 -0.006357** -0.005308* -0.007951** -0.007162 -0.008087* -0.006438 -0.001011 -0.003141

0.002338 0.002557 0.002871 0.003139 0.003997 0.004524 0.004718 0.005213 0.005361 0.0052220.075 0.132 0.028 0.093 0.049 0.116 0.089 0.219 0.851 0.549


Event Window

1

2

3

4

5

Companies registering the largest negative significant impacts are significantly large on average (US$8.5 billion) to be impacted by a market like Venezuela


−.2 −.15 −.1 −.05 0Cummulative Abnormal Returns

MIDDLEBY CORP

AVNET INC

TUPPERWARE BRANDS CORP

LEVEL 3 COMMUNICATIONS INC

MERCADOLIBRE INC

Event 1, Window [-‐3,+3]

−.08 −.06 −.04 −.02 0Cummulative Abnormal Returns

INTERPUBLIC GROUP COS INC

ARVINMERITOR INC

TETRA TECHNOLOGIES INC

INTERVAL LEISURE GROUP INC

BROWN SHOE CO INC NEW

Event 2, Window [-‐3,+3]

Average size: US$8.5 billion

You may find large corporations such as Xerox (market capitalization 10 billion) or Parker Hannifin (US$17.6 billion) ridiculously his by Venezuela devaluations


Event 4, Window [-‐3,+3] Event 5, Window [-‐3,+3]

−.1 −.08 −.06 −.04 −.02 0Cummulative Abnormal Returns

DONNELLEY R R & SONS CO

PARKER HANNIFIN CORP

BIGLARI HOLDINGS INC

HERBALIFE LTD

XEROX CORP

−.15 −.1 −.05 0Cummulative Abnormal Returns

MERCADOLIBRE INC

ACTAVIS PLC

PROGRESS SOFTWARE CORP

TESCO CORP

HERBALIFE LTD

Findings on significant negative cumulative abnormal returns (SNCAR)All sample

• Event 1 (2.15 devalued to 2.60 and 4.30)

• 9 out of 10 event windows have SNCAR

• SNCAR ranging from -‐0.67% to -‐1.48%

• Event 2 (2.60 unified to 4.30)


• Negative abnormal returns ranging from -‐0.71% to -‐1.60%• Event 3 (4.30 devalued to 6.30)

• 1 out of 10 event windows have SNCAR (-‐0.3%)• Event 4 (SICAD I created at 11.30 – first trading day)

• (First) 5 out of 10 event windows have SNCAR• SNCAR ranging from 0.80% to 1.15%

• Event 5 (SICAD II created at 51.86 – first trading day)• 5 out of 10 event windows have SNCAR• SNCAR ranging from 0.40% to 0.80%


Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10] – Non-‐Oil companies


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

-0.007032** !0.006392* -0.010975*** -0.011860** -0.011420** -0.015052*** -0.013987** -0.016811*** -0.013577** -0.014991**0.003002 0.003732 0.003837 0.004663 0.004771 0.005206 0.005521 0.00549 0.005678 0.0059

0.021 0.089 0.005 0.012 0.018 0.005 0.013 0.003 0.018 0.012-0.002733** -0.007559*** -0.014263*** -0.014408*** -0.017218*** -0.015507*** -0.012499*** -0.009203* -0.005396 -0.004331

0.001184 0.001674 0.002179 0.002666 0.003726 0.003983 0.004137 0.004742 0.005252 0.0052720.023 0.000 0.000 0.000 0.000 0.000 0.003 0.054 0.306 0.413

-0.00335** -0.002478 -0.000268 0.003821 0.002905 0.006554 0.004577 -0.001733 -0.003203 -0.0038440.001418 0.002659 0.003141 0.003647 0.003903 0.004653 0.004878 0.005373 0.005877 0.005888

0.020 0.353 0.932 0.297 0.458 0.161 0.350 0.748 0.587 0.515-0.008516*** -0.009827*** -0.008372*** -0.008075* -0.010706** -0.005881 -0.008174 -0.007625 -0.007566 -0.009336

0.002319 0.002649 0.002901 0.004228 0.00536 0.005842 0.006112 0.006474 0.006916 0.007520.000 0.000 0.005 0.058 0.048 0.316 0.183 0.241 0.276 0.217

-0.004162* -0.003816 -0.006173** -0.004814 -0.008041* -0.007750* -0.009069* -0.007245 -0.002953 -0.0055730.00244 0.002669 0.002987 0.003246 0.00414 0.004684 0.0048891 0.005395 0.005518 0.00534

0.091 0.155 0.040 0.141 0.054 0.100 0.066 0.182 0.594 0.299

Coefficients *44p<0.104Robust4Standard4Errors **4p<0.05P!values ***4p<0.01

Event Window

1

2

3

4

5

Findings on significant negative cumulative abnormal returns (SNCAR)Non-‐oil companies

• Event 1 (2.15 devalued to 2.60 and 4.30)


• SNCAR ranging from -‐0.64% to -‐1.68%

• Event 2 (2.60 unified to 4.30)


• Negative abnormal returns ranging from -‐0.27% to -‐1.72%• Event 3 (4.30 devalued to 6.30)

• 1 out of 10 event windows have SNCAR (-‐0.3%)• Event 4 (SICAD I created at 11.30 – first trading day)

• (First) 5 out of 10 event windows have SNCAR• SNCAR ranging from 0.80% to 1.07%

• Event 5 (SICAD II created at 51.86 – first trading day)• 5 out of 10 event windows have SNCAR• SNCAR ranging from 0.40% to 0.08%


Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10] – CADIVI registered (29)


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

-0.0041389 0.0038226 -0.0009887 -0.0005574 0.0001599 -0.0003796 -0.0004936 -0.0023567 0.0023577 -0.00259410.0041284 0.0044083 0.0045014 0.0051943 0.0056337 0.0057265 0.0068232 0.0071439 0.0080047 0.0079145

0.325 0.393 0.828 0.915 0.978 0.948 0.943 0.744 0.771 0.746-0.0004607 -0.0041245 * -0.005048 -0.0053949 -0.005313 -0.0084544 -0.010159 -0.0121606 -0.0077907 -0.01096970.0018738 0.0022068 0.0040547 0.0046174 0.0058087 0.0076095 0.0082239 0.008593 0.0109184 0.010756

0.808 0.072 0.223 0.252 0.368 0.276 0.227 0.168 0.481 0.317-0.0000951 0.0072136 0.0092733 0.0126774 0.012535 0.0137528 0.0143063 0.0182959 * 0.0173738 * 0.0180078 *0.0018724 0.007198 0.0078196 0.0091648 0.0081789 0.0092838 0.0086438 0.0090459 0.0102221 0.0102398

0.960 0.325 0.246 0.178 0.137 0.150 0.109 0.053 0.100 0.090 -0.0116292 * -0.0114415 * -0.0153327 ** -0.0194293 ** -0.0220253 ** -0.0228478 ** -0.0195911 ** -0.0191293 * -0.0156234 -0.0188855 *

0.0062462 0.00586 0.0064258 0.008725 0.0089615 0.009923 0.0088554 0.0103289 0.0098254 0.00982540.073 0.061 0.024 0.034 0.020 0.029 0.035 0.075 0.123 0.066

-0.002062 -0.0021827 -0.0035607 -0.0006737 -0.0064991 -0.0064513 -0.00546 -0.010655 -0.0057554 -0.00772880.0024542 0.003869 0.0051557 0.0050117 0.0084691 0.0098357 0.0095287 0.0120512 0.0125958 0.011221

0.408 0.577 0.495 0.894 0.449 0.517 0.571 0.384 0.651 0.497


Event Window

1

2

3

4

5

Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10] – Non-‐CADIVI (91)


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

-0.007413 ** -0.008174 * -0.012384 * -0.013203 ** -0.012265 ** -0.017381 ** -0.016628 ** -0.01822 *** -0.015599 ** -0.016988 **0.003507 0.004417 0.0047907 0.0059672 0.0061391 0.0067 0.006903 0.006813 0.00686 0.007272

0.037 0.067 0.011 0.029 0.048 0.011 0.018 0.009 0.025 0.021-0.002283 -0.007896 *** -0.015949 *** -0.014816 *** -0.018953 *** -0.015619 *** -0.012650 ** -0.007371 -0.003609 -0.0019440.001453 0.001974 0.0025372 0.0033506 0.0046086 0.0048314 0.004832 0.005602 0.005921 0.006065

0.119 0.000 0.000 0.000 0.000 0.002 0.010 0.191 0.543 0.749 -0.004355 ** -0.005615 ** -0.00433 0.001872 0.000258 0.005025 0.001713 -0.00704 -0.008207 -0.009069

0.001659 0.002545 0.0032092 0.0037385 0.0042859 0.005143 0.005526 0.006025 0.0065845 0.00662070.010 0.030 0.180 0.618 0.952 0.331 0.757 0.245 0.215 0.174

-0.006905 *** -0.008606 *** -0.006281 ** -0.004979 -0.008593 -0.002866 -0.006037 -0.005033 -0.006071 -0.0066840.002301 0.00288 0.0031577 0.0046638 0.0061776 0.006716 0.0071877 0.007541 0.00815 0.0089707

0.003 0.003 0.049 0.288 0.167 0.670 0.403 0.506 0.458 0.458-0.004783 -0.004336 -0.007129 ** -0.006587 * -0.008351 * -0.007358 -0.008812 -0.005273 0.0003 -0.0018740.002908 0.0030904 0.003383 0.0037608 0.004553 0.0051186 0.0054375 0.005787 0.0059199 0.0059223

0.103 0.163 0.037 0.083 0.069 0.154 0.108 0.364 0.960 0.752


Event Window

1

2

3

4

5

Findings

• Significant negative cumulative abnormal returns for devaluations 1, 2 and 4; whose impact can be as high as -‐1.72% on average

1

03/17/2016 BALAS Conference 2016: Most likely casualties of Dutch disease 31

• As expected, impacts are higher and more significant for the non-‐oil sample 2

• For firms registered in CADIVI, only devaluation 4 (SICAD I) have significant negative abnormal returns, although they impact is higher -‐2.20%

3

• For firms not-‐registered in CADIVI, devaluations 1 and 2 are particularly significant, with significant negative abnormal returns as high as 1.89%

4

32




• What happened?

• Conclusions


Data

• We paired each company in our non-‐oil sample with a peer following:

• Firms not having Venezuelan subsidiary that they own more than 25%

• Most similar NAICS code (6-‐digit, if no peers moving back to 4-‐digits)

• Within the range of similar companies, we chose the one with the market capitalization that is closer to our sample firm


Cummulative abnormal returns: From [-‐1,+1] to [-‐10,+10] – Peer sample


Event [-1,+1] [-2,+2] [-3,+3] [-4,+4] [-5,+5] [-6,+6] [-7,+7] [-8,+8] [-9,+9] [-10,+10]

0.000747 -0.001894 -0.006172 -0.001879 -0.002569 -0.001818 -0.00235 -0.006053 0.001316 0.0022230.004338 0.004855 0.005564 0.006535 0.006595 0.006865 0.006908 0.006882 0.007348 0.007509

0.863 0.697 0.269 0.774 0.697 0.792 0.734 0.381 0.858 0.768-0.003694** -0.004455** -0.009809*** -0.004609 -0.009193* -0.010412** -0.007546 -0.003849 -0.000168 0.007598

0.00173 0.002161 0.002988 0.004338 0.004859 0.004686 0.006697 0.007657 0.008372 0.0095130.035 0.041 0.001 0.290 0.061 0.028 0.262 0.616 0.984 0.426

-0.001696 -0.002421 -0.004153 -0.006061 -0.001946 0.004759 -0.002328 -0.018103* -0.0145302 -0.010080.002302 0.002718 0.00493 0.008674 0.007933 0.008131 0.008819 0.010677 0.011509 0.012007

0.740 0.375 0.401 0.486 0.807 0.559 0.792 0.093 0.209 0.403-0.003495 -0.006964* -0.002864 -0.003541 -0.004419 -0.008114 -0.007095 -0.001444 -0.005832 -0.0025030.002946 0.003714 0.004268 0.004841 0.005041 0.005397 0.006237 0.006813 0.007832 0.007479

0.238 0.063 0.503 0.466 0.382 0.135 0.258 0.832 0.458 0.738-0.006578*** -0.007587** -0.003796 0.003125 0.002829 0.000443 0.002254 0.002662 0.000843 -0.006232

0.0022873 0.003167 0.004848 0.005315 0.00639 0.006687 0.006811 0.007382 0.007666 0.0074750.005 0.018 0.435 0.558 0.659 0.947 0.741 0.719 0.913 0.406


Event Window

1

2

3

4

5

35




• What happened?

• Conclusions


36


4.00

5.00

6.00

7.00

8.00

9.00

10.00

11.00

Feb-03

Jun-03

Oct-03

Feb-04

Jun-04

Oct-04

Feb-05

Jun-05

Oct-05

Feb-06

Jun-06

Oct-06

Feb-07

Jun-07

Oct-07

Feb-08

Jun-08

Oct-08

Feb-09

Jun-09

Oct-09

Feb-10

Jun-10

Oct-10

Feb-11

Jun-11

Oct-11

Feb-12

Jun-12

Oct-12

Feb-13

Jun-13

Oct-13

Feb-14

Jun-14

Oct-14

Feb-15

Jun-15

Oct-15

Venezuela:;Inflation,;Devaluation;and;Depreciation(Feb;2003=100,;in;logs)

Inflation Devaluation Depreciation

For many years (2005-‐2010) firms increased prices, costs and profits by inflation, and translated those profits at lagging official exchange rates

Logarithm

ic Scale!

37


38


CADIVI ALDs for dividend repatriation came to a halt by 2009, but profits continued to be recorded at official rates – didn’t need to be in CADIVI to do this!

0

200

400

600

800

1000

1200

III(2007

IV(2007

I(2008

II(2008

III2008

IV(2008

I(2009

II(2009

III2009

IV(2009

I(2010

II(2010

III2010

IV(2010

I(2011

II(2011

III2011

IV(2011

I(2012

II(2012

III2012

IV(2012CADIVI:(Total(Authorization( to(Liquidate(Dollars((ALD)

(US$(million)

Private(External(Debt Foreign(Investment

39


In the meantime, the parallel market started to distance itself significantly from the official exchange rate, eventually by a factor of 10 by 2014, 1000 by 2015!

1

10

100

1000

10000

6$23$2010

8$31$2010

11$25$2010

2$21$2011

5$2$2011

7$4$2011

9$4$2011

11$6$2011

1$8$2012

3$11$2012

5$15$2012

7$16$2012

9$19$2012

11$22$2012

1$24$2013

5$23$2013

7$23$2013

9$22$2013

11$22$2013

1$23$2014

3$26$2014

5$26$2014

7$26$2014

9$25$2014

11$25$2014

1$26$2015

3$29$2015

5$29$2015

7$29$2015

9$30$2015

12$1$2015

1$31$2016

4$1$2016

6$1$2016

8$8$2016

10$8$2016

Venezuela:4Multiple4exchange4rates(VEF4per4US$,42010$2016)

Black4market4XR4rate Official4XR SICAD4I SICAD4II

40




• What happened?

• Conclusions


Conclusions

• We find evidence of significant negative impacts on stock prices on various Venezuelan devaluations, reaching up average across the sample of 2.20% for CADIVI-‐registered firms, -‐1.89% for those not registered over the event window.

• The fact that you did not even have to be registered in CADIVI to register these negative returns is an indication that profits of Venezuelan subsidiaries were largely overvalued in the balance sheet of MNCs, when in fact there was little to no chance of realizing those profits at those official rates

• We find the size of the impacts with respect to the size of the MNCs involved, totally out of proportion with respect to the size of the Venezuelan market, hinting large market myopia

• This is not a paper on window dressing, is a paper on market myopia


Work in progress

• Peer groups can be fine-‐tuned and defined by event, not for the whole sample

• Why the impacts on CADIVI-‐registered companies occur mostly on event 4 (SICAD I), and companies not-‐registered in CADIVI are mostly hit on events 1 and 2?

• Are there any specific industry effects? Any evidence of some industries being more affected than others?


fool´s gold: the case of multinationals in venezuela

Economy & Finance