Swarnali Ahmed Hannan

External Sector Unit

Strategy, Policy and Review Department

International Monetary Fund

Email: sahmed@imf.org

1

Current trade slowdown witnessed in data What drives trade?

What can policy do?

TPP TPP had reinvigorated the debate on the impact of

trade agreements, leading to a rise in research on the ex-ante impact of trade agreements.

Considerable uncertainty involved in ex-ante models need to be complemented by ex-post studies.

Synthetic Control Method Currently, very popular method for micro and macro

studies.

First study to employ SCM across a large number of trade agreements.

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SCM is an econometric tool for comparative studies where the control unit is determined by a systematic data driven procedure.

SCM creates a synthetic (artificial) control unit that is a weighted average or linear combination of the untreated units.

The weights are chosen such that both the outcome variable and its observable covariates/determinants are matched with the treated unit before treatment.

The evolution of the actual outcome of the treated unit post- treatment is then compared against the outcome of the synthetic unit, and the difference is interpreted as the treatment effect.

Intuitively, the SCM basically uses a weighted average of the outcome of the control units to estimate the counterfactual outcome of the treated unit.

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Currently a very popular approach of comparative case studies in both micro and macro studies (e.g. impact of cigarette sales tax, economic impact of German reunification).

Why? A number of methods have been used to deal with the problem of selection bias in observational data, including matching estimators, difference-in-differences regressions, etc.

These techniques are useful but do not deal with unobservable country heterogeneity. At best, control for time-invariant country characteristics (Hosny, 2012).

SCM can allow the effects of unobserved confounders to vary with time (Abadie et al., 2010).

Start off with the typical gravity equation used to model bilateral trade.

xijt = GtMex

it Mimjt φijt

The dependent variables can be regarded as covariates of SCM approach.

Distance between the bilateral pairs

GDP of each country in the bilateral pair

GDP per capita of each country in the bilateral pair

Population of each country in the bilateral pair

Bilateral Real Exchange Rate

Remoteness of each country in the bilateral pair, proxy for multilateral trade resistance (MTR) term (remoteness due to physical distance and/or policy).

Colonial history = 1 if pair ever in colonial relationship

Col to = 1 if export from hegemon to colony

Col from = 1 if export from colony to hegemon

Contig = 1 for contiguity

Comleg = 1 for common legal origins

Comcur = 1 for common currency

Common language = 1 for common official language

Flow, lagged by 3years

Source: Head, Mayer and Ries (2010), WDI, National Sources

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Coverage:

Balanced Sample

1983-1995 104

pairs

Export – Import

For some

exercises also

considered 1973-

2001216 pairs

(All)

26

18

30

30

AM-AM

EM-EM

AM-EM

EM-AM

7

8

The y-axis refers to ten years before and after trade agreement.

0

2000

4000

6000

8000

10000

12000

0

2000

4000

6000

8000

10000

12000

-10 -8 -6 -4 -2 0 2 4 6 8 10

Treated

Synthetic

USD Million

Exports, Average of

104 Country Pairs

9

0

20000

40000

60000

80000

100000

120000

140000

0

20000

40000

60000

80000

100000

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140000

-10 -8 -6 -4 -2 0 2 4 6 8 10

Treated

Synthetic

Exports, Average of All Country Pairs in NAFTA

The y-axis referes to ten years before and after trade agreement.

USD Million

The y-axis refers to ten years before and after trade agreement.

10

0

50000

100000

150000

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250000

300000

350000

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50000

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150000

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350000

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10

U.S. Exports to

Canada and Mexico

Treated Synthetic

USD Million

0

20000

40000

60000

80000

100000

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140000

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0

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-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10

Mexico Exports to

Canada and U.S.

Treated Synthetic

USD Million

The y-axis refers to ten years before and after trade agreement.

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0

20

40

60

80

100

120

EC'86 EM-AM AM-AM EM-EM All NAFTA AM-EM

Export Growth of Average Treated Over Ten Years,

Relative to Average Synthetic (cumulative, percentage points)

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-200

-100

0

100

200

300

400

500

600

700

800

0 0.2 0.4 0.6 0.8 1

Exp

ort

gai

ns

ove

r te

n y

ears

(pp

t)

Goodness of fit between treated and synthetic prior treatment

Size of bubles represents nominal GDP (USD million) of exporting country

during the year of trade agreement. Export gains are export growth of treated over ten years relative to synthetic, in cumulative percentage points.

Goodness of fit is the normalized root-mean-square deviation between treated and synthetic for the ten years prior to treatment. A smaller number of goodness of fit indicates a better fit.

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0

50

100

150

200

250

300

350

400

2 3 5 7

Export Growth Over Ten Years

(cumulative percentage points)

Trade agreements

with higher depth

0

50

100

150

200

250

PTA FTA Customs Union

Export Growth Over Ten Years

(cumulative percentage points)

Trade agreements

with higher depth

Source of trade agreements’ depth:

Left hand chart: Economic Integration Agreement Database (1950-2011), Bergstrand and Baier.

Right hand chart: Dür, Andreas, Leonardo Baccini, and Manfred Elsig. 2014. “The Design of International Trade Agreements:

Introducing a New Database.” Review of International Organizations 9(3), 353-375.

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Import Growth of Average Treated Over Ten Years,

Relative to Average Synthetic (cumulative, percentage points)

-40

-30

-20

-10

0

10

20

30

40

50

60

EM-AM All AM-AM

-What happens to the top importer outside trade agreement?

-Apply SCM to the top importer that is outside the trade agreement.

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Export Growth of Average Treated Over Ten Years,

Relative to Average Synthetic (cumulative, percentage points)

0

5

10

15

20

25

EM-AM All AM-AM

-What happens to the top export destination outside trade agreement?

-Apply SCM to the top export destination that is outside the trade agreement.

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Trade agreements can generate substantial

gains, particularly for emerging markets.

The study falls under a small group of

literature that shows trade agreements

matter!

Relevant for policy making in the current

context of trade slowdown.

The limitations of SCM approach should also

be borne in mind while interpreting these

results.

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Background Slides

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There are J+1 units (regions) in periods t=1,….,T.

Region “one” is exposed to the intervention during periods T0+1 to T.

is the outcome that would be observed for region i at time t in the absence of intervention.

is the outcome that would be observed for region i at time t if region i is exposed to the intervention in periods T0+1 to T.

is the effect of the intervention for unit i at time t for t>T0.

AIM: estimate the effect of the intervention on the treated unit

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Suppose is given by a factor model:

is an unobserved (common) time-dependent factor,

is a vector of observed covariates

is a vector of unknown parameters

is a vector of unknown common factors

is a vector of unknown factor loadings

are unobserved transitory shocks

: heterogeneous responses to multiple unobserved factors.

Basic idea: reweight the control group such that the synthetic control unit matched and (some) pre-treatment of the treated unit, . As a result, is automatically matched.

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Let

Each value of W represents a particular

weighted average of control units.

The value of the outcome variable for each

synthetic control indexed by W is:

Suppose that we can choose W* such that:

Then an unbiased estimator of is

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In practice, the vector is optimally

chosen to minimize the following pseudo-

distance:

where represents a vector of pre-

intervention characteristics of the treated

region, while is a matrix containing the

same pre-intervention variables of the

control regions.

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Background Slides

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Concept:

Assess whether the effect estimated by the synthetic control for a country pair affected by the trade agreement is large relative to the effect estimated for a country pair chosen at random.

Process:

Randomly select 10 treated units.

Let A = exporter in the treated unit.

Randomly select 5 country pairs showing the exports of A to a country not in the trade agreement (placebo).

Run SCM on these selected country pairs.

Compare treated relative to synthetic for treated unit versus the placebo unit.

Example:

Treated unit is CAD USA (one of the 10 randomly chosen treated unit).

Here, CAD is the exporter in the treated unit.

Take CAD, and randomly choose 5 country pairs showing CAD exports to other partners not in trade agreement (placebos).

Run SCM on each randomly chosen country pair.

Compare treated relative synthetic of CAD USA with that of the 5 placebo units.

Results show one

failure only: one

case where

treated unit is

greater than its

synthetic AND

placebo unit shows

greater treated

relative to

synthetic unit.

-300

-200

-100

0

100

200

300

400

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

10

-20000

0

20000

40000

60000

80000

100000

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

10

-1500

-1000

-500

0

500

1000

1500

-10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9

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Treated (or Placebo) relative to

Synthetic. Black line is treated, others placebo

Examples of Successful

Placebo tests

Background Slides

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Country Pairs

Exporting

country

Importing

country

Year of Trade

Agreement*

Exporting

country

Importing

country

Year of Trade

Agreement*

1 AUS NZL 1983 27 IDN MYS 1992

2 NZL AUS 1983 28 IDN PHL 1992

3 AUT ESP 1986 29 IDN SGP 1992

4 BEL ESP 1986 30 IDN THA 1992

5 CHE ESP 1986 31 MYS IDN 1992

6 DEU ESP 1986 32 MYS PHL 1992

7 ESP AUT 1986 33 MYS SGP 1992

8 ESP BEL 1986 34 MYS THA 1992

9 ESP CHE 1986 35 PHL IDN 1992

10 ESP DEU 1986 36 PHL MYS 1992

11 ESP FRA 1986 37 PHL SGP 1992

12 ESP IRL 1986 38 PHL THA 1992

13 ESP ITA 1986 39 SGP IDN 1992

14 ESP NLD 1986 40 SGP MYS 1992

15 ESP NOR 1986 41 SGP PHL 1992

16 ESP PRT 1986 42 SGP THA 1992

17 ESP SWE 1986 43 THA IDN 1992

18 FRA ESP 1986 44 THA MYS 1992

19 IRL ESP 1986 45 THA PHL 1992

20 ITA ESP 1986 46 THA SGP 1992

21 NLD ESP 1986 47 AUT HUN 1993

22 NOR ESP 1986 48 AUT POL 1993

23 PRT ESP 1986 49 CHE HUN 1993

24 SWE ESP 1986 50 CHE POL 1993

25 CAN USA 1989 51 HUN AUT 1993

26 USA CAN 1989 52 HUN CHE 1993

*Entry into force

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Country Pairs

Exporting

country

Importing

country

Year of Trade

Agreement*

Exporting

country

Importing

country

Year of Trade

Agreement*

53 HUN NOR 1993 79 HUN ITA 1994

54 HUN POL 1993 80 HUN NLD 1994

55 HUN SWE 1993 81 HUN PRT 1994

56 NOR HUN 1993 82 IRL HUN 1994

57 NOR POL 1993 83 IRL POL 1994

58 POL AUT 1993 84 ITA HUN 1994

59 POL CHE 1993 85 ITA POL 1994

60 POL HUN 1993 86 MEX CAN 1994

61 POL NOR 1993 87 MEX USA 1994

62 POL SWE 1993 88 NLD HUN 1994

63 SWE HUN 1993 89 NLD POL 1994

64 SWE POL 1993 90 POL BEL 1994

65 BEL HUN 1994 91 POL DEU 1994

66 BEL POL 1994 92 POL ESP 1994

67 CAN MEX 1994 93 POL FRA 1994

68 DEU HUN 1994 94 POL IRL 1994

69 DEU POL 1994 95 POL ITA 1994

70 ESP HUN 1994 96 POL NLD 1994

71 ESP POL 1994 97 POL PRT 1994

72 FRA HUN 1994 98 PRT HUN 1994

73 FRA POL 1994 99 PRT POL 1994

74 HUN BEL 1994 100 USA MEX 1994

75 HUN DEU 1994 101 COL MEX 1995

76 HUN ESP 1994 102 COL PER 1995

77 HUN FRA 1994 103 MEX COL 1995

78 HUN IRL 1994 104 PER COL 1995

*Entry into force