The Caribbean and its Linkages with the World: A GVAR Model Approach1

Mauricio Vargas; Daniela Hess

doi:10.5089/9781498326766.001.A001

Jump to Content Jump to Main Navigation

The Caribbean and its Linkages with the World: A GVAR Model Approach¹

Author: Mr. Mauricio Vargas¹ and Daniela Hess²

¹ 0000000404811396https://isni.org/isni/0000000404811396International Monetary Fund
| ² 0000000404811396https://isni.org/isni/0000000404811396International Monetary Fund

Publication Date:: 27 Nov 2019

eISBN:: 9781498326766

Language:: English

Keywords:: WP; exchange rate; oil price shock; commodity exporter country; commodity-exporter country; ECCU tourism source country; tourism source market

Download PDF (6.8 MB)

Using data from 1980-2017, this paper estimates a Global VAR (GVAR) model taylored for the Caribbean region which includes its major trading partners, representing altogether around 60 percent of the global economy. We provide stilyzed facts of the main interrelations between the Caribbean region and the rest of the world, and then we quantify the impact of external shocks on Caribbean countries through the application of two case studies: i) a change in the international price of oil, and ii) an increase in the U.S. GDP. We confirmed that Caribbean countries are highly exposed to external factors, and that a fall in oil prices and an increase in the U.S. GDP have a positive and large impact on most of them after controlling for financial variables, exchange rate fluctuations and overall price changes. The results from the model help to disentangle effects from various channels that interact at the same time, such as flows of tourists, trade of goods, and changes in economic conditions in the largest economies of the globe.

Abstract

I. Introduction

Global spillovers are a central element in international economics, and Caribbean countries are as acutely exposed to them as many others. Production and trade in goods and services, and financial flows depend not only on internal market supply and demand forces, but also on competitiveness and world growth. During the past decades, many small and large countries have leaned towards trade openness and financial liberalization and some evidence suggests that this might benefit their economies (Edwards, 1997; Meissner, 2014). Notwithstanding, a strong degree of integration poses additional risks to small open economies that may suffer disproportionately from shifting economic conditions in the largest economies of the globe, as they are less able to diversify away from the sectors in which they have comparative advantages; that is the case for most Caribbean countries which are highly internationally integrated, especially through tourism flows—a sector often hit hard by downturns in larger economies.

To quantify the strength of macroeconomic linkages between Caribbean countries and the rest of the world, we introduce a Caribbean-tailored Global Vector Auto-regressive (GVAR) model. GVAR models were first introduced by Pesaran, Schuermann, and Weinner (2004) and further developed by Dees, di Mauro, Pesaran, and Smith (2007). Our GVAR model features 45 developing, emerging market, and advanced economies, of which 15 are Caribbean. The analysis focusses on specific spillovers for Caribbean countries, such as the effect of an expansionary policy in the United States or an oil price drop. One of the main advantages of implementing a GVAR model to assess macroeconomic impacts of external shocks is that it allows to internalize second round effects that are usually considered as exogenous or static in less sophisticated models. In a GVAR model, an external shock and its dynamics can be included endogenously in the final model.

Our paper is linked to various companion papers that have utilized GVAR models to gauge the effect of global and country-specific shock scenarios and investigates macroeconomic linkages between selected countries and the region and the rest of the world. In this context, Galesi and Lombardi (2009) investigate the effects of oil and food prices shocks on inflation and find that the inflationary effects of oil price shocks are more sizable on developed countries than on emerging economies. Using a GVAR model of global trade flows, Bussiere, Chudik, and Sestieri (2012) measure the effect on trade flows of various shocks and conclude that changes in domestic and foreign demand have a much stronger effect on trade flows as compared with changes in relative trade prices.

An additional advantage of the GVAR methodology is that it allows the inclusion of global variables, such as oil or raw material prices, in a unified framework to account for its effects on particular countries or regions. Oil and other commodity prices are an important observed common factor in GVAR models examining the factors affecting growth dynamics. Chudik and Fidora (2012) investigate the impact that supply-induced oil price increases have on aggregate output and real effective exchange rates and find that adverse oil supply shocks have considerable negative effects on real output growth of oil importers (and that emerging economies are more affected than advanced economies). They also conclude that oil supply shocks tend to cause an appreciation (depreciation) of oil exporters’ (oil importers’) real effective exchange rates and an appreciation of the U.S. dollar. Similarly, in the midst of large fluctuations in commodity prices and ongoing structural changes relating to globalization, Anderton et al. (2010) utilized a GVAR model to investigate how oil price shocks feed through core and headline inflation and conclude that there seem to be significant pressures on global trade prices and labor markets associated with structural factors that are partly due to globalization.

The GVAR approach has been applied as well to highlight regional or country-specific scenarios. ² Cesa-Bianchi, Pesaran, Rebucci, and Xu (2011) focus on the emergence of China as a key player in the global economy and investigate how fluctuations in trade patterns between China and the rest of the world may have altered the transmission mechanisms of the international business cycle to Latin America. They find that the long-term impact of a China GDP shock on the typical Latin American country has tripled since the mid-1990s, while the long-run effect of a U.S. GDP shock has halved. On a similar regional approach, Han and Hee Ng (2011) implement a GVAR model to examine macroeconomic forecasts for the ASEAN-5 countries³. They find that GVAR forecasts tend to outperform forecasts based on the benchmark country-specific models, especially for short-term interest rates and real equity prices.

This paper is organized as follows: in Section II we present stylized facts of the main linkages between Caribbean countries and the largest economies in the world. Section III briefly describes the GVAR methodology and the dataset. Our main results and case studies are explained in Section IV. Finally, Section V concludes and proposes potential further developments.

II. Stylized Facts

Caribbean countries are integrated into the global economy mainly through their dependence on tourist arrivals and/or their position as goods exporters. Within our sample of 15 Caribbean economies, we classify Antigua and Barbuda, the Bahamas, Barbados, Belize, Dominica, Dominican Republic, Grenada, Jamaica, St. Kitts and Nevis, St. Lucia, and St. Vincent and the Grenadines as tourism-dependent countries, while Haiti, Guyana, Suriname, and Trinidad and Tobago are classified as goods exporters.

Although most Caribbean countries depend heavily on tourist flows, just three of them account for three-quarters of all tourist arrivals.⁴ As of 2015, the Dominican Republic, Jamaica, and the Bahamas received almost 74 percent of the total number of visitors to the region. On the other hand, Dominica, St. Vincent and the Grenadines, and St. Kitts and Nevis have a share of tourist arrivals of just 2.1 percent of the regional total. In 2015, 78 percent of tourists arrived from Europe, Canada, and the U.S., while the remaining 22 percent include a significant proportion of intraregional visitors. In terms of single countries, the United States is the most important source of visitors to the Caribbean, accounting for 42 percent of total stay-over tourists.

Caribbean tourism-dependent countries face broad and recurrent merchandise trade deficits that are to some extent counterbalanced by positive net services flows. By end-2017, tourism-dependent countries average exports of goods reached 9.0 percent of GDP, well below their average exports of services which represented 36.7 percent. Moreover, Caribbean countries’ imports of goods were relatively high, exceeding the 30 percent of GDP in most of the cases.

Commodity exporter countries clearly depend less on their export of services and more heavily on their exports of goods; the top export destination of this group are OECD countries (and Latin America and the Caribbean (LAC) in the case of Trinidad and Tobago). The average exports of goods for the group of commodity-exporter countries is 38.7 percent of GDP, while its average exports of services are around 5.4 percent.

Table 1.

Current Account and Trade of Goods and Services (as percent of GDP, 2017)

Source: IMF estimates based on WEO.

^{^a\}Unweighted averages.

Table 1.

Current Account and Trade of Goods and Services (as percent of GDP, 2017)

	Current Account Balance	Goods Balance	Services Balance	Exports		Imports
	Current Account Balance	Goods Balance	Services Balance	Goods	Services	Goods	Services
Caribbean average ^a\	-5.5	-18.6	11.7	16.9	28.3	35.5	16.6
Tourism-Dependent average ^a\	-7.5	-25.2	19.0	9.0	36.7	34.2	17.7
Commodity Exporter average ^a\	-0.1	-0.3	-8.1	38.7	5.4	39.0	13.5

Source: IMF estimates based on WEO.

^{^a\}Unweighted averages.

Table 1.

Current Account and Trade of Goods and Services (as percent of GDP, 2017)

	Current Account Balance	Goods Balance	Services Balance	Exports		Imports
	Current Account Balance	Goods Balance	Services Balance	Goods	Services	Goods	Services
Caribbean average ^a\	-5.5	-18.6	11.7	16.9	28.3	35.5	16.6
Tourism-Dependent average ^a\	-7.5	-25.2	19.0	9.0	36.7	34.2	17.7
Commodity Exporter average ^a\	-0.1	-0.3	-8.1	38.7	5.4	39.0	13.5

Source: IMF estimates based on WEO.

^{^a\}Unweighted averages.

The current account balance has been persistently negative in Caribbean countries, especially for the tourism-dependent countries. Current account deficits represented 5.5 percent of GDP in 2017 for tourism-dependent countries, while for commodity-exporter countries the current account is almost balanced at -0.1 percent of GDP. As a result of a low degree of diversification across the region, total imports represented around 52 percent of GDP with no significant differences between tourism-dependent and commodity-exporter groups.

In light of strong external linkages, it is not surprising that Caribbean economic activity fluctuates in tandem with that of its trading partners. Indeed, at least 9 out of the 15 Caribbean countries show a strong and positive correlation of their GDP growth with that of Canada, the United States and/or the United Kingdom (see Figure 4), with The Bahamas, Barbados, and Antigua and Barbuda being the most dependent. On the other hand, three countries that have faced important episodes of natural disasters in recent years, possibly distorting the link, show the weakest association (namely: Haiti, Guyana, and Dominica).

III. Methodology and Data

Methodology

We tailored the Smith and Galesi (2014) GVAR Matlab toolbox to fit Caribbean countries’ characteristics and data availability. The GVAR methodology can be summarized in a couple of intuitive steps; however, to be implemented numerically, it requires complex coding and programming of large datasets that are not yet incorporated in any econometric software. Smith and Galesi (2014) developed a Matlab toolbox that has provided support to various related empirical applications, including in this research.

A GVAR model tackles the dimensionality problem of including more than one country in an econometric system by following a two-stage procedure Working with more than one country in an integrated context usually faces the infeasibility of specifying a unique Vector Autoregressive (VAR) model including all of them in a unified system. The implementation of the following two steps avoids this problem: i) estimating separate models for each country, and ii) linking them through their trade relationships in a global and integrated model.

The first step consists on estimating several individual VAR-X models, more precisely, one for each of the countries included in the sample. Thus, for country i with i = 0,1,2..N (where country 0 is considered as a reference country), our benchmark VAR-X model is specified as:

\begin{matrix} x_{i, t} = a_{i 0} + a_{i 1} t + Φ_{i 1} x_{i, t - 1} + \dots + Φ_{ip} x_{i, t - p_{i}} + Λ_{i 0} x_{i, t}^{*} + Λ_{iq} x_{i, t - 1}^{*} + \dots + Λ_{iq} x_{i, t - q_{i}}^{*} + u_{i, t} & (1) \\ x_{i, t} : k_{i} \times 1 vector of domestic variables \\ x_{i, t}^{*} : k_{i}^{*} \times 1 vector of foreign variables \end{matrix}

Where p and q represent the lag order of the domestic and foreign variables, respectively. In addition, foreign variables are defined as weighted averages of each country’s trading-partners:

\begin{matrix} x_{i, t}^{*} = Σ_{j = 0}^{N} w_{i, j} x_{j, t} & w_{i, i} = 0 \end{matrix}

With w_i,j, j = 0,1,..., N stand for the weights such that $Σ_{j = 0}^{N} w_{i, j} = 1$ .

While the second stage involves the specification of a global system based on the estimates of the individual VARX models, and the matrix of trade weights. Since all the variables are endogenous to the system as a whole, then the model can be solved in terms of a k × 1 global variable vector $(k = Σ_{i = 0}^{N} k_{i})$ , thus we define:

z_{i, t} = (\begin{matrix} x_{i, t} \\ x_{i, t}^{*} \end{matrix})

For didactic purposes, we can assume that p = q , in which case equation (1) can be expressed as:

\begin{matrix} A_{i 0} z_{i, t} = a_{i 0} + a_{i 1} t + A_{i 1} z_{i, t - 1} + \dots + A_{i, p_{i}} z_{i, t - p_{i}} + u_{i, t} & (2) \end{matrix}

Where

\begin{matrix} \begin{matrix} A_{io} = (I_{k_{i}} - Λ_{i 0}), & A_{i, j} = (Φ_{i, j}, Λ_{i, j}) \end{matrix} & for j = 1, \dots, p_{i} \end{matrix}

It can be proved that, for each country i, a matrix W_i composed by trade weights w_i,j exists such that the following identity holds:

\begin{matrix} z_{i, t} = {(x_{it}^{'}, x_{it}^{*}')}^{'} = W_{i} x_{t} & (3) \end{matrix}

Where $x_{t} = {(x_{0 t}^{'}, x_{1 t}^{'}, \dots, x_{Nt}^{'})}^{'}$ is the k × 1 vector containing all the endogenous variables of the system and W_i is a $(k_{i} + k_{i}^{*}) \times k$ matrix. Replacing (3) in (2) we obtain:

\begin{matrix} \begin{matrix} A_{i 0} W_{i} x_{t} = a_{i 0} + a_{i 1} t + A_{i 1} W_{i} x_{t - 1} + \dots + A_{{ip}_{i}} W_{i} x_{t - p_{i}} + u_{it}, & for i = 0, 1, 2, \dots, N \end{matrix} & (4) \end{matrix}

Stacking the N+1 models:

\begin{matrix} G_{0} x_{t} = a_{0} + a_{1} t + G_{1} x_{t - 1} + \dots + G_{p} x_{t - p} + u_{t} & (5) \end{matrix}

Where:

\begin{array}{l} \begin{matrix} \begin{matrix} \begin{matrix} \begin{matrix} G_{0} = (\begin{matrix} \begin{matrix} \begin{matrix} A_{00} W_{0} \\ A_{10} W_{1} \end{matrix} \end{matrix} \\ A_{N 0} W_{N} \end{matrix}), \end{matrix} \end{matrix} & G_{j} = (\begin{matrix} \begin{matrix} \begin{matrix} A_{0 j} W_{0} \\ A_{1 j} W_{1} \end{matrix} \\ M \end{matrix} \\ A_{N j} W_{N} \end{matrix}) \end{matrix} & for j = 1, \dots, p \end{matrix} \\ \begin{matrix} \begin{matrix} a_{0} = (\begin{matrix} \begin{matrix} \begin{matrix} a_{00} \\ a_{10} \end{matrix} \\ M \\ a_{N 0} \end{matrix} \end{matrix}), \end{matrix} & \begin{matrix} \begin{matrix} \begin{matrix} a_{1} = (\begin{matrix} \begin{matrix} \begin{matrix} a_{01} \\ a_{11} \end{matrix} \\ M \\ a_{N 1} \end{matrix} \end{matrix}), \end{matrix} \end{matrix} & u_{t} \end{matrix} = (\begin{matrix} u_{0 t} \\ \begin{matrix} \begin{matrix} u_{1 t} \\ M \end{matrix} \\ u_{Nt} \end{matrix} \end{matrix}) \end{matrix} \end{array}

And p = max p_i across all i . G₀ is a matrix which depends on trade weights and the parameter estimates from each individual VAR-X model. Then, (5) can be re-expressed as a standard VAR model:⁵

\begin{matrix} x_{t} = b_{0} + b_{1} t + F_{1} x_{t - 1} + \dots + F_{p} x_{t - p} + ε_{t} & (6) \end{matrix}

Where

\begin{array}{l} b_{0} = G_{0}^{- 1} a_{0}, & b_{1} = G_{0}^{- 1} a_{1} \\ F_{j} = G_{0}^{- 1} G_{j}, & \begin{matrix} \begin{matrix} j = 1, \dots, p, \end{matrix} & ε_{t} = G_{0}^{- 1} u_{t} \end{matrix} \end{array}

Data and Model Specification

We propose a GVAR model based on annual data for 44 countries, of which 15 belong to the Caribbean region. ⁶ The choice of annual frequency, between 1980 and 2017, corresponds to shortfalls of quarterly information in several Caribbean countries. The database contains four country-specific variables: real gross domestic product (GDP, y_i,t), real exchange rate (rer_i,t), interest rates (r_i,t) and inflation (π_i,t); two global variables, namely, oil price (poil_t) and price of raw materials (pmat_t); and a set of exports (exp_i,j,t) and imports (imp_i,j,t) for each country i disaggregated by origin and destination from/to the other remaining j countries.

Specifically, each of the above variables are defined for each country i and year t as:

y_i,t = ln (Real _ GDP_i,t) : Real _ GDP_i,t is the real GDP in dollars (base year 2010)
rer_i,t = e_i,t – p_i,t
e_i,t = ln(E_i,t) : E_i,t is the Exchange Rate (National currency per U.S. dollar)
p_i,t = ln (CPI_i,t) : CPI_i,t is the Consumer price index (base year 2010).
r_i,t = R_i,t/100 : R_i,t is the interest rate in percent per year.
π_i,t = p_i,t – p_i,t-1
poil_i,t = ln (WTI_i,t) : WTI_i,t is the WTI oil price in U.S. dollars.
pmat_i,t = ln (Raw _ materials _ price _ index_i,t)
exp_i,j,t : Value of Exports from country i to country j in period t
imp_i,j,t : Value of Imports to country i from country j in period t.

Then, the general specification for each country specific VAR-X model considers:

\begin{matrix} x_{i, t} & = (y_{i, t}, {rer}_{i, t}, r_{i, t}, π_{i, t}) \\ x_{i, t}^{*} & = (y_{i, t}^{*}, {rer}_{i, t}^{*}, r_{i, t}^{*}, π_{i, t}^{*}, poil, pmat) \end{matrix}

IV. Results

Estimates and Tests

Several statistical and economic considerations should be taken into account for a proper specification of a GVAR model. Since this global model uses the estimates of each individual country’s VARX as inputs, ensuring compliance of certain desirable statistical and economic properties is needed. The benchmark specification, which includes lags of all the variables in the system, was adjusted according to stability and statistical significance of each specific model. In practical terms, one of the main reasons to exclude a variable of a particular country’s model was to avoid its negative impact on country-specifics and global stability (e.g. nominal variables in countries that experienced large inflation episodes). As a result, not every individual model includes the same set of variables or lags.

Weak exogeneity assumption of foreign variables is central to allow country models to be estimated individually. A formal test of this assumption for country-specific foreign variables and global variables in each of the individual VARX models was conducted along the lines described in Johansen (1992) and Harbo et al. (1998). The results, shown in the Annex, Table A1, suggest that weak exogeneity hypothesis could not be rejected for most of the variables included in the sub-systems; indeed, only 5 out of 212 exogeneity tests performed reject the weak exogeneity hypothesis.

Table A1.

Weak Exogeneity Test

Table A1.

Weak Exogeneity Test

Country	F test	Fcrit_0.05	gdps	Dps	eps	rs	poil
ANTIGUA AND BARBUDA	F(1,23)	4.28	1.24	2.42	0.01	0.26	0.92
AUSTRIA	F(1,22)	4.30	0.64		0.39	0.04
BAHAMAS	F(1,23)	4.28	2.47	0.71	0.47	4.40	1.11
BARBADOS	F(1,23)	4.28	0.03	1.54	0.32	1.46	0.18
BELGIUM	F(1,22)	4.30	0.63	5.38	0.08	0.48	1.63
BELIZE	F(1,23)	4.28	0.02	0.44	0.00	0.15	0.15
BULGARIA	F(1,23)	4.28	1.24	0.65	0.41	0.37	0.01
CAMEROON	F(1,22)	4.30	0.96	0.23	0.03	0.05	0.56
CANADA	F(1,22)	4.30	0.43	1.14	0.41	1.38	0.02
CHINA	F(1,24)	4.26	0.24	1.04	0.66	0.28	1.31
CYPRUS	F(1,23)	4.28	0.21	0.12	1.54	0.01	0.00
DENMARK	F(1,22)	4.30	1.30	0.91	0.61	0.06	0.05
DOMINICA	F(1,23)	4.28	3.25	0.12	0.30	0.41	0.81
DOMINICAN REPUBLIC	F(1,23)	4.28	0.98	0.29	0.02	0.07	0.07
FINLAND	F(1,22)	4.30	0.49	3.14	0.82	2.09	0.11
FRANCE	F(1,22)	4.30	1.23	0.71	0.08	0.99	1.42
GERMANY	F(1,22)	4.30	0.38	0.14	0.32	0.20	1.62
GREECE	F(1,22)	4.30	3.52	0.97	0.00	1.87
GRENADA	F(1,23)	4.28	0.00	0.41	0.52	1.39	0.11
GUYANA	F(1,22)	4.30	2.17	0.54	0.60	3.07	0.52
HAITI	F(1,23)	4.28	0.73	0.13	0.51	1.61	0.28
HUNGARY	F(1,22)	4.30	0.37	0.07	0.03	0.46	1.71
INDIA	F(1,22)	4.30	0.01	0.00	0.20	0.92	0.42
IRELAND	F(1,22)	4.30	4.70	0.29	0.03	1.42	0.00
ITALY	F(1,22)	4.30	0.59	0.53	0.25	1.36	0.00
JAMAICA	F(1,22)	4.30	0.05	0.00	0.14	0.24	0.13
JAPAN	F(1,22)	4.30	0.38	0.96	0.03	0.62	3.44
LUXEMBOURG	F(1,22)	4.30	0.54	1.22	0.19	0.07	0.35
MALTA	F(1,23)	4.28	0.03			0.00
MEXICO	F(1,23)	4.28	2.38	3.65	0.31	0.03	5.61
NETHERLANDS	F(1,22)	4.30	0.05	0.29	10.18	0.00	0.00
POLAND	F(1,23)	4.28	0.00	0.18	0.10	0.04	0.01
PORTUGAL	F(1,22)	4.30	0.21	0.01	0.22	0.07	0.28
ROMANIA	F(1,23)	4.28	0.01	0.02	0.06	0.28	0.17
SINGAPORE	F(1,22)	4.30	2.15	1.49	3.31	0.00	2.73
SPAIN	F(1,22)	4.30	2.66	0.05	0.00	0.01
ST. KITTS AND NEVIS	F(1,23)	4.28	0.11	0.31	1.16	0.04	2.35
ST. LUCIA	F(1,23)	4.28	0.17	0.53	1.48	0.37	0.40
ST. VINCENT AND THE GRENADINES	F(1,23)	4.28	0.00	1.01	2.05	0.31	0.25
SURINAME	F(1,23)	4.28	1.37	2.62	0.26	1.00	0.05
SWEDEN	F(1,22)	4.30	0.32	1.53	0.13	0.06	0.04
TRINIDAD AND TOBAGO	F(1,22)	4.30	0.01	0.48	0.83	0.65	0.02
UNITED KINGDOM	F(1,22)	4.30	0.04	3.76	0.88	2.94	0.80
USA	F(1,23)	4.28	2.62	1.11	1.57	0.01

Table A1.

Weak Exogeneity Test

Country	F test	Fcrit_0.05	gdps	Dps	eps	rs	poil
ANTIGUA AND BARBUDA	F(1,23)	4.28	1.24	2.42	0.01	0.26	0.92
AUSTRIA	F(1,22)	4.30	0.64		0.39	0.04
BAHAMAS	F(1,23)	4.28	2.47	0.71	0.47	4.40	1.11
BARBADOS	F(1,23)	4.28	0.03	1.54	0.32	1.46	0.18
BELGIUM	F(1,22)	4.30	0.63	5.38	0.08	0.48	1.63
BELIZE	F(1,23)	4.28	0.02	0.44	0.00	0.15	0.15
BULGARIA	F(1,23)	4.28	1.24	0.65	0.41	0.37	0.01
CAMEROON	F(1,22)	4.30	0.96	0.23	0.03	0.05	0.56
CANADA	F(1,22)	4.30	0.43	1.14	0.41	1.38	0.02
CHINA	F(1,24)	4.26	0.24	1.04	0.66	0.28	1.31
CYPRUS	F(1,23)	4.28	0.21	0.12	1.54	0.01	0.00
DENMARK	F(1,22)	4.30	1.30	0.91	0.61	0.06	0.05
DOMINICA	F(1,23)	4.28	3.25	0.12	0.30	0.41	0.81
DOMINICAN REPUBLIC	F(1,23)	4.28	0.98	0.29	0.02	0.07	0.07
FINLAND	F(1,22)	4.30	0.49	3.14	0.82	2.09	0.11
FRANCE	F(1,22)	4.30	1.23	0.71	0.08	0.99	1.42
GERMANY	F(1,22)	4.30	0.38	0.14	0.32	0.20	1.62
GREECE	F(1,22)	4.30	3.52	0.97	0.00	1.87
GRENADA	F(1,23)	4.28	0.00	0.41	0.52	1.39	0.11
GUYANA	F(1,22)	4.30	2.17	0.54	0.60	3.07	0.52
HAITI	F(1,23)	4.28	0.73	0.13	0.51	1.61	0.28
HUNGARY	F(1,22)	4.30	0.37	0.07	0.03	0.46	1.71
INDIA	F(1,22)	4.30	0.01	0.00	0.20	0.92	0.42
IRELAND	F(1,22)	4.30	4.70	0.29	0.03	1.42	0.00
ITALY	F(1,22)	4.30	0.59	0.53	0.25	1.36	0.00
JAMAICA	F(1,22)	4.30	0.05	0.00	0.14	0.24	0.13
JAPAN	F(1,22)	4.30	0.38	0.96	0.03	0.62	3.44
LUXEMBOURG	F(1,22)	4.30	0.54	1.22	0.19	0.07	0.35
MALTA	F(1,23)	4.28	0.03			0.00
MEXICO	F(1,23)	4.28	2.38	3.65	0.31	0.03	5.61
NETHERLANDS	F(1,22)	4.30	0.05	0.29	10.18	0.00	0.00
POLAND	F(1,23)	4.28	0.00	0.18	0.10	0.04	0.01
PORTUGAL	F(1,22)	4.30	0.21	0.01	0.22	0.07	0.28
ROMANIA	F(1,23)	4.28	0.01	0.02	0.06	0.28	0.17
SINGAPORE	F(1,22)	4.30	2.15	1.49	3.31	0.00	2.73
SPAIN	F(1,22)	4.30	2.66	0.05	0.00	0.01
ST. KITTS AND NEVIS	F(1,23)	4.28	0.11	0.31	1.16	0.04	2.35
ST. LUCIA	F(1,23)	4.28	0.17	0.53	1.48	0.37	0.40
ST. VINCENT AND THE GRENADINES	F(1,23)	4.28	0.00	1.01	2.05	0.31	0.25
SURINAME	F(1,23)	4.28	1.37	2.62	0.26	1.00	0.05
SWEDEN	F(1,22)	4.30	0.32	1.53	0.13	0.06	0.04
TRINIDAD AND TOBAGO	F(1,22)	4.30	0.01	0.48	0.83	0.65	0.02
UNITED KINGDOM	F(1,22)	4.30	0.04	3.76	0.88	2.94	0.80
USA	F(1,23)	4.28	2.62	1.11	1.57	0.01

Case Studies

We applied our Caribbean-tailored GVAR model to two case studies. In the first one, we quantify the impact of the recent drop in oil prices on countries in the Eastern Caribbean Currency Union (ECCU), a group of net oil importers, contrasting, at the same time, the impact on their major tourism source markets, which are oil producers; the second study case estimates the implication of an expansionary policy in the U.S. by assuming a positive shock on the U.S. GDP. In this case, we describe potential channels of transmission and quantify the short- and medium-term effects on economic activity in the Caribbean countries.

A. Oil price spillovers to ECCU countries.

Oil price variations might remold the global scenario and shift benefits and costs between countries and regions. Most studies agree that the effects of oil price shocks on economic activity vary according to several elements. Monetary policy and whether the shock is positive or negative, or supply or demand-driven matter (Hamilton, 1996; Bernanke et al., 1997), as well as the condition of a country as a net oil-importer or exporter, or its degree of diversification (Ferderer, 1996).

ECCU countries are characterized by being net oil importers, dependent on tourism and are not very diversified. Thus, a variation in a global variable, such as the decline in oil prices observed since mid-2014, represents fertile ground to analyze its impact on GDP. On the one hand, cheaper oil prices would benefit net oil-importer economies in terms of lower costs of imports, price of energy and transport, and thus higher household real income. On the other hand, lower oil prices might negatively affect economic activity in tourism source countries that are oil exporters (e.g. U.S., Canada, and U.K.) and are not much diversified (e.g. Trinidad and Tobago⁷). Together, this could ultimately weaken the demand for tourism services and therefore lead to lower GDP levels in ECCU countries.

As expected, the fall in oil prices since mid-2014 benefitted ECCU countries by pulling down both the value of imports and fuel inflation. Imports of oil in the region were reduced by about 4 percentage points of GDP, improving current account balances. In the same direction, energy prices were clearly contained between 2014-2016. A lower oil price affected not only the price of fuel, but also the price of electricity which follows best practice by passing fuel costs on to consumers⁸. In general, ECCU countries adjust fuel prices to end-consumers monthly by taking into account an average of the past three-months, therefore there is a certain lag to reflect current variations of prices in the import market. While not the only mechanism in place, the fall of oil prices could represent an income transfer from oil exporter countries to net oil importers, thus leading to an increase in consumption spending in ECCU countries and an expansion of aggregate demand.

The impact of lower oil prices on activity of the main ECCU tourism source markets was mixed. Economic growth of net oil-exporter countries, such as Trinidad and Tobago and Canada, was affected in 2015 and 2016⁹. After a slowdown in the GDP growth rate from 2.5 percent in 2014 to 1.2 in 2015, Canada managed the situation by implementing accommodative fiscal and monetary policies, including exchange rate depreciation. In the case of Trinidad of Tobago, the impact of lower oil prices was stronger within the energy sector, which represents one quarter of the economy. This led to a recession of about 10 percent in 2016 in that sector, implying a negative overall growth in 2016 and 2017 of -6.1 and -2.6 percent, respectively. The effect on other important ECCU tourism source markets, which are more diversified, such as the United States or the United Kingdom was less clear. The UK, despite being a net oil importer, is the third largest producer of oil and gas in Europe just after the Russian Federation and Norway. Notwithstanding the direct negative effect of lower oil prices on the oil and gas extraction sector, other UK economic sectors such as agriculture, air transport, refined petroleum, and oil-intensive manufacturing sectors (PWC, 2015) were expected to outweigh the initial negative impact, with uncertain net benefits for the overall economy. A similar ambiguous scenario occurred in the U.S. where oil investments were cut in half between the period 2014 and 2017, and it’s not clear if a boost to consumption and non-oil investment was fully enough to outweigh the negative impact on investment in the energy sector (IMF, 2016).

With regard to tourist flows to ECCU countries, growth of stay-over arrivals from the main tourism source countries slowed but stayed at positive rates, except those from Canada. Indeed, the fall in the oil price coincided with a pronounced drop of 11 percent (y-o-y) of Canadian tourist arrivals to the ECCU region in 2015.

Results from our GVAR model suggest that an oil price drop positively affects economic activity in the ECCU region. The GVAR model is helpful to gauge the overall impact of an oil price drop on economic activity in the ECCU countries after controlling for the mechanisms described in previous paragraphs. The model is capable of simulating GDP changes due to a global shock affecting all of the countries included in it, while capturing contagious effects through the use of trading partner weights. The Figure below shows the Impulse-Response functions of a negative oil price shock equivalent to 20 percent in its price. A positive response of GDP is expected in all ECCU countries but Dominica, whose results might be sensitive to the recent large natural disasters. Indeed, owing to the impact of Tropical storm Erika (2015) and hurricane Maria (2017), Dominica’s economy collapsed precisely during the same time-span of the latest fall of oil prices (2014-2017)¹⁰. The model also predicts an initial negative impact on tourism source economies, which diminishes over time. The ECCU tourism source country that is expected to be negatively affected the most is Trinidad and Tobago, where an oil shock would hit the economy in a big way, by about 2 percent of GDP in the medium term. This magnitude coincides with the decline observed in 2016-2017.

B. The Potential Impact of an Expansionary Policy Stance in the U.S.

The relative weight of the United States in the global economy has weakened slightly during the past four decades, mainly due to the strong growth of China, India, and other emerging economies. Nonetheless, in 2017, the U.S. economy represented 24.3 percent of global GDP and around 12 percent of global trade. The U.S. impact on the global system is not limited to its predominance in production and trade; indeed it might be magnified by its central role in the International Monetary System (Gourinchas and Rey, 2007). Contrasting with the relevance of the United States in global terms, the Caribbean aggregated GDP fluctuated between 0.12 and 0.29 percent of world GDP since 1980, and was around 0.2 percent in 2017—a small economy, even when considered as a region.

U.S. tourists are very important for Caribbean tourism-dependent countries. Forty-seven percent of total tourists to the region arrived from the U.S. in 2016. As a region, this share has been stable since 2006 and corresponds mainly to a large number of tourists visiting Belize, the Dominican Republic, and The Bahamas. In addition to those countries, U.S. visitors are relatively more important for the tourism sector in St. Kitts and Nevis, even though tourist arrivals from the U.S. to this country are relatively low in absolute terms.

Among goods-exporting Caribbean countries, trade with the U.S. is important as well. The U.S. has been the main destination of Haitian and Trinidad and Tobago exports, representing, on average between 1980 and 2017, 79 and 51 percent of their total exports, respectively. With regards to imports from the United States in the set of goods-exporter countries, they have been decreasing somewhat as a share of total imports since the early 2000s, yet they represented about 20-30 percent of their total imports in 2017.

Notwithstanding its global influence, U.S. GDP, tourists, and trade are not the only channels affecting Caribbean economies; exchange rate regimes and interest rate parity matter as well. Most Caribbean countries have pegged or relatively rigid exchange rate regimes with respect to the U.S. dollar (see Figure 2a). A stronger U.S. dollar would increase the cost of Caribbean country exports, including tourism, for non-U.S. countries; thereby adversely affecting tourists to CARICOM countries who as a whole are mainly non-U.S. Additionally, Caribbean imports from countries that are not pegged to the U.S. dollar might become more competitive, widening further the recurrent deficits in their trade balances. With regard to interest rates, the link between domestic and foreign interest rates in the Caribbean seems to be elusive, at least for ECCU countries. According to Myrvoda and Reynaud (2018), and IMF (2018), ECCU interest rates may not respond significantly to variations in external interest rates. Statistical results from the GVAR model support those findings.

After controlling for the various transmission mechanisms from the U.S. to the rest of the world, our GVAR model suggests that the Caribbean countries would highly benefit from an expansionary policy stance in the U.S. All tourism-dependent Caribbean countries would increase their level of GDP in response to a positive shock in economic activity in the U.S., a few of them even more than proportionally to the change in the U.S. GDP. On the other hand, the size of the impact could be marginally null or negative for some good-exporters, including Trinidad and Tobago¹¹ and Haiti while it is expected to be positive for Suriname and Guyana. Although Haiti and Trinidad and Tobago show a larger exposure to trade flows with the U.S. than other countries such as Suriname, the model predicts a lower response of those two countries to a U.S. GDP positive shock. This apparently counterintuitive result is explained by a larger response of those countries to real exchange rate fluctuations that accompany the initial GDP shock, and spread to all other countries, partially reverting the initial trade effect.

V. Conclusions and Policy Implications

Measuring linkages between different regions of the globe is a challenge. However, the GVAR methodology shows itself to be useful to condense large amounts of information in a way that permits researchers to isolate global shocks or country-specific shocks and gauge their impact across the board.

Given its size and large dependence of external markets, the Caribbean region is particularly sensitive to policy changes or shocks in large trading partners, such as the U.S., Canada, or the U.K. While most of the Caribbean countries can be classified as tourism dependent, a few others are also affected by external conditions due to the significant size of their trade in goods.

An oil price drop would benefit the economies of most ECCU countries. We applied our GVAR model to simulate a global oil price drop. The GVAR model IRFs suggest that an oil price shock might negatively affect important ECCU trading partners that are oil exporters, such the U.K., Canada, and Trinidad and Tobago, while an initial negative effect on GDP followed by a recovery in the medium term would be expected in the U.S. Overall, and given their condition as oil importers, our findings reveal that most ECCU economies would expect a positive impact on their GDP. Those results coincide with the outcome from the recent drop in oil prices in 2014.

Also, we found a strong impact from an expansionary policy in the U.S. on most Caribbean economies. Simulated by a positive shock on the domestic GDP of the U.S., an expansionary policy would strongly affect tourism-dependent economies while having mixed effects on the set of Caribbean goods exporters. The results are not surprising given the relevance of U.S. tourist flows for the region and contribute to confirming results from country-specific models while taking into account a richer set of interactions.

External shocks represent a large source of uncertainty and volatility to small states and structural policies might help to downgrade their impact. While the questions raised in this paper are not new to IMF’s Staff Reports and research papers, the GVAR methodology represents an alternative way to tackle them in a more integrated fashion while including second round effects from the dynamics of trading partners. The observed large impact of external factors suggest that Caribbean countries may benefit from preventive measures such as increasing competitiveness, diversifying their economies and reducing their dependence on critical commodities and services, namely, oil-based energy and tourism. These policies might reduce exposure to external imbalances and, at the same time, promote economic growth.

The GVAR methodology is capable of providing responses to a broad range of questions. The model represents a promising avenue for empirical analysis and could be expanded to include more countries or idiosyncratic variables for particular countries. We leave this as a potential extension for future research.

References

Anderton R. and Alessandro Galesi and Marco Lombardi and Filippo di Mauro, 2010. “Key Elements of Global Inflation,” RBA Annual Conference Volume,in: Renée Fry and Callum Jones and Christopher Kent (ed.), Inflation in an Era of Relative Price Shocks Reserve Bank of Australia
- Search Google Scholar
- Export Citation
Baumeister C. and Lutz Kilian, 2016. “Lower Oil Prices and the U.S. Economy: Is This Time Different?,” Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 47(2 (Fall)), pages 287-357.
- Search Google Scholar
- Export Citation
Bernanke B.and Mark Gertler and Mark Watson, 1997. “Systematic Monetary Policy and the Effects of Oil Price Shocks,” Brookings Papers on Economic Activity, Economic Studies Program, The Brookings Institution, vol. 28(1), pages 91-157.
- Search Google Scholar
- Export Citation
Chudik A. and Michael Fidora, 2012. “How the global perspective can help us identify structural shocks,” Staff Papers, Federal Reserve Bank of Dallas, issue Dec.
- Search Google Scholar
- Export Citation
Chudik A. and M. Hashem Pesaran, 2013. “Econometric Analysis of High Dimensional VARs Featuring a Dominant Unit,” Econometric Reviews, Taylor and Francis Journals, vol. 32(5-6), pages 592-649, August.
- Search Google Scholar
- Export Citation
Chudik A. and M. Hashem Pesaran, 2016. “Theory and Practice Of Gvar Modelling,” Journal of Economic Surveys, Wiley Blackwell, vol. 30(1), pages 165-197, 02.
- Search Google Scholar
- Export Citation
Di Mauro F. and L. Vanessa Smith and Stephane Dees and M. Hashem Pesaran, 2007. “Exploring the international linkages of the euro area: a global VAR analysis,” Journal of Applied Econometrics, John Wiley and Sons, Ltd., vol. 22(1), pages 1-38.
- Search Google Scholar
- Export Citation
Edwards Sebastian, 1997.”Openness, Productivity and Growth: What Do We Really Know?,” NBER Working Papers 5978, National Bureau of Economic Research.
- Search Google Scholar
- Export Citation
Ferderer, Peter, 1996. “Oil price volatility and the macroeconomy,” Journal of Macroeconomics, Elsevier, vol. 18(1), pages 1-26.
- Search Google Scholar
- Export Citation
Gourinchas P. and Hélène Rey, 2007. “From World Banker to World Venture Capitalist: U.S. External Adjustment and the Exorbitant Privilege,” NBER Chapters, in: G7 Current Account Imbalances: Sustainability and Adjustment, pages 11-66, National Bureau of Economic Research, Inc.
- Search Google Scholar
- Export Citation
Hamilton, James D., 1996. “This is what happened to the oil price-macroeconomy relationship,” Journal of Monetary Economics, Elsevier, vol. 38(2), pages 215-220, October.
- Search Google Scholar
- Export Citation
Han, Fei and Ng, Thiam, (2011), ASEAN-5 Macroeconomic Forecasting Using a GVAR Model, No 76, Working Papers on Regional Economic Integration, Asian Development Bank.
- Search Google Scholar
- Export Citation
Harbo, I., S. Johansen, B. Nielsen, and A. Rahbek. 1998. ‘Asymptotic Inference on Cointegrating Rank in Partial Systems’, Journal of Business and Economic Statistics, 16, pp. 388-399.
- Search Google Scholar
- Export Citation
IMF, 2016. ‘IMF Country Report 16/226’, July.
- Search Google Scholar
- Export Citation
IMF, 2018. ‘IMF Country Report 18/179’, June.
- Search Google Scholar
- Export Citation
Johansen, S. 1992. ‘Cointegration in Partial Systems and the Efficiency of Single-Equation Analysis’, Journal of Econometrics, 52, pp. 231-254.
- Search Google Scholar
- Export Citation
Meissner, Christopher M., 2014. “Growth from Globalization? A View from the Very Long Run,” Handbook of Economic Growth, in: Handbook of Economic Growth, edition 1, volume 2, chapter 8, pages 1033-1069 Elsevier.
- Search Google Scholar
- Export Citation
Myrvoda A. and Julien Reynaud, 2018. “Monetary Policy Transmission in the Eastern Caribbean Currency Union,“ IMF Working Papers 18/70, International Monetary Fund.
- Search Google Scholar
- Export Citation
Pesaran, M. Hashem and Schuermann, Til and Smith, L. Vanessa, 2009. “Forecasting economic and financial variables with global VARs,” International Journal of Forecasting, Elsevier, vol. 25(4), pages 642-675, October.
- Search Google Scholar
- Export Citation
PwC, 2015. “The Impact of Lower Oil Prices on the UK Economy”, on UK Economic Outlook, March 2015.
- Search Google Scholar
- Export Citation
Raciborski R. and Anastasia Theofilakou and Lukas Vogel, 2015. “Revisiting the macroeconomic effects of oil price changes,” Quarterly Report on the Euro Area (QREA), Directorate General Economic and Financial Affairs (DG ECFIN), European Commission, vol. 14(2), pages 19-27, July.
- Search Google Scholar
- Export Citation
Walther T. and Lanouar Charfeddine and Tony Klein, 2018. “Oil Price Changes and U.S. Real GDP Growth: Is this Time Different?” Working Papers on Finance 1816, University of St. Gallen, School of Finance.
- Search Google Scholar
- Export Citation

Annex

List of countries included in the model

1 Antigua and Barbuda

2 Austria

3 Bahamas

4 Barbados

5 Belgium

6 Belize

7 Bulgaria

8 Cameroon

9 Canada

10 China

11 Cyprus

12 Denmark

13 Dominica

14 Dominican Republic

15 Finland

16 France

17 Germany

18 Greece

19 Grenada

20 Guyana

21 Haiti

22 Hungary

23 India

24 Ireland

25 Italy

26 Jamaica

27 Japan

28 Luxembourg

29 Malta

30 Mexico

31 Netherlands

32 Poland

33 Portugal

34 Romania

35 Singapore

36 Spain

37 St. Kitts and Nevis

38 St. Lucia

39 St. Vincent and the Grenadines

40 Suriname

41 Sweden

42 Trinidad and Tobago

43 United Kingdom

44 United States

Table A2.

Coefficients of the VECX Model

ANTIGUA AND BARBUDA	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.47 0.77 0.09	0.23 1.49 -0.07	0.00 0.03 0.00	-0.21 -1.32 0.06	-0.17 -1.04 0.05	-0.03 -0.18 0.01	0.02 0.12 -0.01	-0.01 -0.05 0.00	-0.10 -0.64 0.03	0.00 0.00 0.00	1.66 -0.26 -0.02	-0.16 0.09 0.03	-0.19 -0.12 -0.01	2.90 0.13 -0.14	-0.05 0.01 0.00
AUSTRIA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	eps_1	rs_1	dgdps_0	deps_0	drs_0
dgdp dDp dep dr	0.75 0.40 0.98 0.75	-0.71 -0.47 -0.90 -0.09	-0.28 -0.18 -0.35 -0.03	-0.35 -0.23 -0.44 -0.04	0.16 0.11 0.20 0.02	0.08 0.05 0.10 0.01	0.31 0.20 0.38 0.04	-0.17 -0.11 -0.22 -0.02	0.55 0.36 0.69 0.07	0.80 0.36 0.41 -0.02	-0.01 0.01 1.18 0.00	0.24 0.35 0.27 0.77
BAHAMAS	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.41 0.64 0.30	0.47 0.78 0.24	0.06 0.10 0.03	-0.36 -0.58 -0.18	-0.30 -0.49 -0.15	-0.07 -0.11 -0.03	0.24 0.38 0.12	-0.02 -0.02 -0.01	0.16 0.26 0.08	0.00 0.00 0.00	0.76 -0.25 -0.09	-1.01 0.96 0.01	0.03 -0.03 0.00	0.47 -0.21 0.08	0.04 -0.02 0.00
BARBADOS	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.50 0.53 0.71	-0.11 0.43 -0.04	-0.05 0.19 -0.02	0.17 -0.70 0.06	-0.51 2.07 -0.18	0.02 -0.09 0.01	-0.18 0.74 -0.06	0.00 -0.01 0.00	0.54 -2.19 0.19	0.01 -0.02 0.00	0.77 -0.16 0.01	1.00 0.50 -0.27	0.07 -0.15 -0.09	0.85 0.54 0.78	-0.03 0.03 0.01
BELGIUM	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.84 0.79 0.96 0.64	0.29 -0.57 0.30 -0.39	-0.31 0.61 -0.32 0.42	0.21 -0.42 0.22 -0.29	-0.03 0.06 -0.03 0.04	-0.04 0.08 -0.04 0.05	0.22 -0.43 0.22 -0.29	-0.11 0.22 -0.11 0.15	0.02 -0.05 0.02 -0.03	-0.03 0.05 -0.03 0.04	0.00 0.00 0.00 0.00	0.67 0.26 -0.04 0.21	0.16 0.70 0.14 0.48	-0.01 0.04 1.23 0.01	0.18 -0.30 0.19 0.48	0.00 0.01 0.01 -0.01
BELIZE	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.39 0.79 0.05	0.55 0.40 -0.03	0.14 0.11 -0.01	-0.97 -0.72 0.06	-0.15 -0.11 0.01	-0.08 -0.06 0.01	1.14 0.85 -0.07	0.09 0.07 -0.01	0.28 0.21 -0.02	0.02 0.01 0.00	0.92 0.18 -0.09	-0.12 0.83 -0.05	-0.03 0.12 -0.02	-1.23 -0.23 0.21	0.03 0.04 0.00
BULGARIA	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.87 0.20 0.09	-1.01 3.01 0.80	-0.06 0.19 0.04	0.03 -0.10 -0.02	-0.01 0.04 0.01	0.16 -0.49 -0.10	-0.48 1.48 0.29	0.18 -0.54 -0.11	-0.19 0.58 0.11	0.04 -0.13 -0.02	0.71 3.69 -8.00	-0.43 5.96 0.69	0.02 0.91 0.53	1.25 -12.30 12.36	0.02 0.23 -0.18
CAMEROON	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.69 0.12 0.64 0.12	0.95 0.05 -0.97 -0.10	0.10 0.00 -0.10 -0.01	-0.14 0.00 0.14 0.02	0.31 0.01 -0.31 -0.04	0.51 0.01 -0.51 -0.06	-0.18 -0.01 0.18 0.02	0.98 0.03 -1.00 -0.11	-0.35 -0.01 0.36 0.04	-0.96 -0.03 0.98 0.11	0.02 0.00 -0.02 0.00	0.55 -0.33 0.50 -0.23	0.51 0.18 -0.03 0.00	0.03 -0.05 1.40 0.01	-1.80 3.62 0.77 0.31	0.01 -0.06 0.01 0.00
CANADA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.81 0.72 0.60 0.75	0.19 0.35 0.99 0.36	0.14 0.24 0.73 0.26	-0.33 -0.56 -1.68 -0.61	0.01 0.01 0.04 0.02	-0.16 -0.27 -0.80 -0.29	-0.14 -0.23 -0.70 -0.25	0.03 0.05 0.16 0.06	-0.03 -0.06 -0.17 -0.06	0.19 0.32 0.95 0.34	0.00 0.00 -0.01 0.00	0.94 -0.32 0.26 -0.04	0.28 0.48 -0.12 0.06	0.03 0.00 0.64 -0.03	-0.08 0.15 -1.40 0.71	0.01 0.00 -0.09 0.00
CHINA	R2	Intercept	gdp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dep	0.44 0.59	1.29 -7.75	0.11 -0.70	0.13 -0.83	-0.28 1.74	0.32 -2.04	0.02 -0.15	0.10 -0.66	0.02 -0.12	0.54 1.51	-1.17 -3.54	0.00 -0.82	-0.58 0.07	0.03 -0.09
CYPRUS	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.60 0.71 0.95	-0.90 0.65 -0.40	-0.18 0.13 -0.08	0.83 -0.60 0.38	-0.15 0.11 -0.07	0.23 -0.17 0.11	-0.43 0.32 -0.20	0.10 -0.07 0.04	0.32 -0.23 0.14	-0.03 0.02 -0.01	1.02 0.20 -0.26	-0.21 0.12 0.21	-0.06 0.02 0.99	1.24 0.28 0.95	-0.02 0.03 -0.03
DENMARK	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.67 0.52 0.96 0.45	-0.14 0.09 -0.11 0.07	-0.12 0.10 -0.10 0.07	0.68 -0.53 0.55 -0.36	-0.05 0.04 -0.04 0.03	-0.25 0.20 -0.20 0.14	0.11 -0.09 0.09 -0.06	0.05 -0.04 0.04 -0.03	0.06 -0.04 0.05 -0.03	0.34 -0.27 0.28 -0.18	0.00 0.00 0.00 0.00	1.47 -0.10 0.68 -0.47	-0.26 0.14 -0.09 0.28	0.00 0.01 1.24 -0.02	-0.71 0.08 -0.29 0.92	0.00 0.01 0.04 0.00
DOMINICA	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.39 0.79 0.15	-0.69 0.83 0.09	-0.21 0.25 0.03	0.70 -0.85 -0.09	1.61 -1.97 -0.20	0.06 -0.07 -0.01	-0.61 0.74 0.08	-0.11 0.13 0.01	0.01 -0.02 0.00	0.00 0.00 0.00	0.17 0.62 -0.03	0.56 0.93 -0.15	-0.50 0.09 0.02	0.39 -1.10 -0.03	-0.05 0.01 0.00
DOMINICAN REPUBLIC	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.23 0.17 0.21	-0.73 -1.88 3.29	-0.04 -0.11 0.19	-0.16 -0.39 0.70	0.09 0.23 -0.41	0.10 0.26 -0.46	0.37 0.92 -1.62	-0.04 -0.10 0.18	0.09 0.22 -0.39	0.01 0.02 -0.04	0.97 1.35 -1.19	-0.71 2.77 3.45	-0.01 0.31 0.36	-0.04 -1.31 -3.15	0.01 0.07 -0.06
FINLAND	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.87 0.56 0.89 0.59	-0.07 0.01 0.08 -0.01	0.05 -0.02 -0.09 0.01	0.26 -0.10 -0.51 0.04	0.07 -0.03 -0.14 0.01	-0.96 0.36 1.85 -0.15	-0.03 0.01 0.06 -0.01	-0.33 0.12 0.64 -0.05	-0.03 0.01 0.05 0.00	0.91 -0.34 -1.75 0.14	0.01 0.00 -0.01 0.00	1.33 0.27 1.01 0.17	0.68 0.24 -0.72 -0.24	0.00 0.02 1.12 0.00	-0.41 -0.41 -2.85 0.98	0.01 0.02 0.05 0.01
FRANCE	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.80 0.45 0.98 0.43	0.00 0.00 0.00 0.00	-0.04 0.18 -0.12 -0.04	0.17 -0.82 0.54 0.20	-0.02 0.09 -0.06 -0.02	-0.28 1.31 -0.87 -0.32	0.04 -0.19 0.12 0.05	-0.03 0.14 -0.10 -0.04	0.02 -0.10 0.07 0.03	0.16 -0.77 0.51 0.19	0.00 0.01 0.00 0.00	0.77 -0.20 0.33 0.03	0.07 0.32 -0.20 -0.02	0.00 0.05 1.18 0.01	0.35 0.27 0.32 0.24	-0.01 0.02 0.01 0.00
GERMANY	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.80 0.49 0.97 0.65	-1.06 -0.33 -1.62 -0.26	0.04 0.01 0.06 0.01	-0.66 -0.20 -0.99 -0.16	-0.19 -0.06 -0.29 -0.05	-0.28 -0.09 -0.43 -0.07	0.09 0.03 0.13 0.02	0.48 0.15 0.72 0.12	0.28 0.09 0.42 0.07	0.31 0.10 0.47 0.08	0.03 0.01 0.04 0.01	0.95 0.14 1.14 0.10	0.14 0.08 0.51 0.11	0.00 0.01 1.37 -0.01	0.93 0.23 -1.74 0.21	0.00 0.02 0.05 0.00
GREECE	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	dgdps_0	dDps_0	deps_0	drs_0
dgdp dDp dep dr	0.51 0.60 0.87 0.43	-1.98 -1.88 1.56 -0.12	0.09 0.09 -0.07 0.01	-0.55 -0.53 0.45 -0.03	0.24 0.23 -0.19 0.01	-0.82 -0.79 0.67 -0.05	0.20 0.19 -0.17 0.01	0.19 0.18 -0.16 0.01	-0.15 -0.15 0.13 -0.01	1.70 1.64 -1.39 0.10	1.53 0.10 1.23 0.37	0.12 0.12 -0.49 0.00	-0.03 -0.01 1.08 0.04	-1.39 0.27 -1.02 0.66
GRENADA	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.54 0.51 0.23	-5.61 -1.53 -0.37	-0.53 -0.14 -0.03	-1.32 -0.35 -0.09	-0.95 -0.25 -0.06	0.90 0.24 0.06	3.04 0.81 0.20	0.22 0.06 0.01	-0.02 0.00 0.00	-0.08 -0.02 -0.01	0.54 0.64 -0.05	0.92 1.32 -0.23	0.41 0.04 0.02	0.43 -0.39 -0.14	-0.01 -0.02 0.00
GUYANA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.60 0.27 0.11 0.52	-0.69 -0.71 0.04 0.39	-0.16 -0.17 0.01 0.09	-0.37 -0.40 0.02 0.20	-0.03 -0.03 0.00 0.02	0.85 0.93 -0.04 -0.45	0.13 0.14 -0.01 -0.07	0.39 0.43 -0.02 -0.21	-0.11 -0.12 0.01 0.06	0.08 0.09 0.00 -0.04	0.00 0.00 0.00 0.00	0.62 -2.24 -0.40 -0.72	-0.05 -0.04 1.94 0.11	0.16 -1.15 -0.15 -0.01	0.28 5.92 1.06 1.21	0.02 -0.01 -0.04 0.01
HAITI	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.40 0.72 0.16	1.54 -4.62 1.51	0.09 -0.27 0.09	0.24 -0.73 0.25	-0.15 0.47 -0.16	-0.19 0.60 -0.20	-0.54 1.66 -0.57	0.09 -0.28 0.10	-0.18 0.55 -0.19	0.01 -0.02 0.01	-0.76 0.87 -0.11	0.21 1.93 -0.54	-0.26 0.34 -0.13	0.93 -2.48 -2.70	-0.02 -0.04 -0.04
HUNGARY	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.76 0.33 0.78 0.42	1.50 0.22 1.52 -0.45	-0.26 -0.04 -0.26 0.08	-0.51 -0.07 -0.51 0.16	-0.06 -0.01 -0.06 0.02	-0.07 -0.01 -0.07 0.02	-0.01 0.00 -0.01 0.00	-0.07 -0.01 -0.07 0.02	-0.01 0.00 -0.01 0.00	0.08 0.01 0.08 -0.03	-0.02 0.00 -0.02 0.01	0.87 -0.23 -0.49 -0.68	0.14 0.07 -0.24 0.19	-0.03 -0.06 0.89 -0.17	-0.97 4.08 1.32 5.49	0.01 -0.04 -0.07 -0.06
INDIA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.20 0.58 0.08 0.15	0.45 1.69 -0.99 -0.05	-0.02 -0.08 0.04 0.00	-0.25 -1.07 0.63 0.03	-0.01 -0.05 0.03 0.00	-0.10 -0.41 0.24 0.01	-0.03 -0.11 0.07 0.00	-0.38 -1.61 0.94 0.05	-0.08 -0.35 0.21 0.01	0.32 1.39 -0.82 -0.04	-0.01 -0.02 0.01 0.00	0.21 0.26 -0.65 -0.09	-0.59 -1.13 0.74 -0.40	-0.12 -0.22 0.22 -0.04	0.93 -0.58 0.21 0.18	-0.01 -0.02 -0.03 0.01
IRELAND	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0	dgdps_1	dDps_1	deps_1	drs_1	dpoil_1
dgdp dDp dep dr	0.62 0.77 0.94 0.58	0.50 0.19 -0.08 0.25	0.12 0.05 -0.02 0.06	-0.91 -0.38 0.15 -0.47	0.54 0.23 -0.09 0.28	-0.71 -0.30 0.11 -0.36	-0.16 -0.07 0.03 -0.08	0.90 0.37 -0.14 0.46	-0.59 -0.25 0.10 -0.30	2.16 0.90 -0.35 1.11	0.02 0.01 0.00 0.01	2.04 0.35 1.15 -0.14	0.41 0.65 1.36 -0.17	0.14 -0.02 1.27 -0.11	1.93 0.37 -0.10 1.21	-0.09 0.00 -0.06 0.00	-0.27 0.09 -1.10 0.05	-0.46 0.23 0.91 -0.94	-0.25 -0.08 -0.21 -0.06	-0.92 -1.18 0.33 -0.52	-0.00923 -0.00416 -0.0178 0.019832
ITALY	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.96 0.36 0.83 0.47	0.70 -0.34 -1.20 -0.09	-0.15 0.07 0.25 0.02	-0.09 0.04 0.15 0.01	0.01 -0.01 -0.03 0.00	-0.34 0.16 0.57 0.04	0.05 -0.02 -0.09 -0.01	0.01 -0.01 -0.02 0.00	0.00 0.00 -0.01 0.00	0.78 -0.37 -1.31 -0.10	0.00 0.00 0.00 0.00	0.97 0.12 0.31 -0.02	0.12 -0.11 -0.46 -0.16	0.01 -0.01 1.17 -0.01	0.16 0.85 1.64 1.65	0.00 0.01 -0.01 0.00
JAMAICA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.27 0.45 0.12 0.31	-0.34 1.66 -0.14 0.63	-0.27 1.33 -0.08 0.50	0.12 -0.59 0.04 -0.22	-0.08 0.40 -0.02 0.15	0.17 -0.83 0.05 -0.31	0.13 -0.63 0.04 -0.24	0.12 -0.60 0.04 -0.23	0.11 -0.52 0.03 -0.20	-0.05 0.24 -0.01 0.09	0.00 0.00 0.00 0.00	-0.01 1.22 0.29 0.41	0.40 -2.76 -1.89 -1.05	-0.14 -0.04 0.67 0.21	0.50 -4.64 -1.63 -1.55	-0.01 0.12 0.08 0.03
JAPAN	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.49 0.47 0.27 0.46	1.68 -0.63 -3.30 -0.30	-0.30 0.11 0.61 0.06	0.79 -0.30 -1.59 -0.14	-0.06 0.02 0.11 0.01	0.55 -0.21 -1.11 -0.10	0.12 -0.05 -0.24 -0.02	-0.34 0.13 0.68 0.06	0.09 -0.03 -0.18 -0.02	0.22 -0.08 -0.44 -0.04	-0.01 0.00 0.03 0.00	0.29 0.08 -1.24 -0.08	0.21 0.27 -3.94 0.07	0.00 -0.01 0.31 0.03	0.44 0.04 4.64 0.12	0.01 0.01 0.10 0.00
LUXEMBOURG	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.67 0.78 0.96 0.45	0.23 -2.04 0.37 -0.11	0.02 -0.17 0.03 -0.01	0.12 -1.07 0.19 -0.06	-0.02 0.19 -0.03 0.01	0.10 -0.95 0.17 -0.05	-0.04 0.35 -0.06 0.02	-0.01 0.05 -0.01 0.00	0.02 -0.19 0.03 -0.01	-0.22 1.99 -0.35 0.11	0.00 0.02 0.00 0.00	1.72 0.54 -0.31 -0.12	-0.93 0.46 1.36 -0.25	0.01 0.03 1.18 0.00	1.25 -1.17 0.25 1.04	-0.01 0.04 -0.03 0.00
M ALTA	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	rs_1	dgdps_0	drs_0
dgdp dDp dep	0.27 0.44 0.15	0.91 0.97 1.94	0.10 0.11 0.22	-0.58 -0.64 -1.28	-0.04 -0.04 -0.08	-0.14 -0.16 -0.32	0.32 0.35 0.71	0.23 -0.06 -0.58	0.59 0.63 -1.84
MEXICO	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.71 0.67 0.74	-0.18 1.34 1.10	-0.25 1.67 1.29	0.09 -0.63 -0.49	-0.05 0.35 0.27	0.21 -1.44 -1.11	1.33 -8.92 -6.90	-0.02 0.13 0.10	-0.21 1.43 1.10	-0.01 0.09 0.07	0.70 -3.74 -4.90	1.46 -5.25 -5.40	0.33 -0.90 -0.85	-0.63 2.65 6.76	0.01 0.09 -0.10
NETHERLANDS	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.85 0.63 0.96 0.10	-0.34 -0.31 0.31 -0.06	0.07 0.06 -0.07 0.01	-0.54 -0.51 0.55 -0.08	0.17 0.16 -0.17 0.03	0.14 0.13 -0.14 0.02	-0.02 -0.01 0.02 0.00	0.26 0.24 -0.26 0.04	-0.17 -0.16 0.17 -0.03	0.18 0.16 -0.18 0.03	0.00 0.00 0.00 0.00	1.26 0.10 0.68 0.18	0.17 0.39 0.38 0.26	0.01 0.03 1.29 0.00	-0.41 0.00 -0.12 -0.76	0.00 0.00 0.02 0.00
POLAND	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.55 0.46 0.62	1.88 17.24 9.69	-0.03 -0.27 -0.15	-0.03 -0.29 -0.17	-0.05 -0.43 -0.24	-0.21 -1.93 -1.09	-0.10 -0.89 -0.50	-0.03 -0.32 -0.18	-1.08 -9.84 -5.57	-0.01 -0.13 -0.08	0.28 -9.33 -5.56	-0.13 -0.79 2.78	0.00 0.19 0.08	-1.50 37.84 7.72	0.02 -0.22 -0.25
PORTUGAL	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.72 0.50 0.98 0.34	-0.14 -0.05 0.25 -0.07	0.08 0.03 -0.15 0.04	0.17 0.07 -0.31 0.09	0.21 0.08 -0.38 0.11	-0.16 -0.06 0.28 -0.08	-0.03 -0.01 0.05 -0.01	0.42 0.16 -0.77 0.21	-0.27 -0.11 0.49 -0.14	-0.14 -0.06 0.26 -0.07	-0.02 -0.01 0.04 -0.01	1.11 0.04 0.05 -0.18	0.09 1.17 -0.37 0.38	-0.03 0.09 1.12 0.04	0.44 0.09 0.35 0.42	-0.03 0.00 0.02 0.01
ROMANIA	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.16 0.51 0.60	-0.07 -3.94 4.94	-0.01 -0.37 0.45	0.00 -0.21 0.26	0.01 0.81 -0.99	0.01 0.73 -0.89	0.02 1.27 -1.56	-0.01 -0.60 0.73	-0.03 -1.88 2.30	0.00 0.17 -0.21	1.03 -3.94 -1.36	0.21 3.60 0.78	-0.13 -0.05 0.56	-1.83 4.03 -3.22	0.03 -0.03 -0.07
SINGAPORE	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.51 0.79 0.49 0.81	0.78 0.14 -1.76 0.67	0.11 0.02 -0.24 0.09	-0.13 -0.02 0.28 -0.11	0.02 0.00 -0.05 0.02	-0.77 -0.15 1.74 -0.67	-0.16 -0.03 0.37 -0.14	0.31 0.06 -0.69 0.26	-0.05 -0.01 0.10 -0.04	0.20 0.04 -0.45 0.17	0.00 0.00 0.00 0.00	1.06 0.33 0.06 -0.08	-0.87 1.82 0.31 0.62	-0.06 0.00 0.39 0.02	1.86 -0.55 -0.06 0.29	0.06 0.01 -0.09 -0.02
SPAIN	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	dgdps_0	dDps_0	deps_0	drs_0
dgdp dDp dep dr	0.64 0.48 0.92 0.40	0.00 0.02 0.02 0.08	0.00 -0.02 -0.02 -0.06	-0.06 -0.31 -0.32 -1.01	-0.02 -0.08 -0.09 -0.27	-0.03 -0.18 -0.18 -0.57	0.00 0.02 0.02 0.05	-0.03 -0.15 -0.15 -0.49	0.02 0.10 0.10 0.33	0.10 0.49 0.49 1.57	1.28 -0.01 -0.02 -0.22	0.06 0.18 -0.68 0.26	-0.03 0.00 1.28 -0.07	-0.07 1.23 -0.11 1.48
ST. KITTS AND NEVIS	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp	0.39	0.99	0.08	-0.97	1.03	-0.14	-0.49	-0.06	1.65	0.03	-0.01	-0.10	0.13	1.47	0.01
dDp dr	0.51 0.14	0.69 0.03	0.06 0.00	-0.70 -0.03	0.75 0.03	-0.10 0.00	-0.36 -0.02	-0.05 0.00	1.20 0.06	0.02 0.00	-0.32 0.05	-0.15 0.07	-0.01 0.03	1.22 -0.03	0.04 0.00
ST. LUCIA	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.22 0.78 0.08	0.24 0.43 -0.01	0.03 0.05 0.00	-0.49 -0.95 0.02	0.44 0.85 -0.02	-0.04 -0.08 0.00	0.18 0.36 -0.01	-0.03 -0.06 0.00	0.35 0.69 -0.01	0.01 0.01 0.00	0.20 -0.40 0.07	-0.38 0.97 -0.23	-0.44 -0.23 0.04	1.43 0.95 -0.26	-0.06 -0.01 0.01
ST. VINCENT AND THE GR	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr S	0.38 0.69 0.34	-0.02 0.49 0.07	0.00 0.07 0.01	0.03 -0.80 -0.12	0.06 -1.84 -0.27	0.00 -0.06 -0.01	0.00 0.08 0.01	0.00 0.04 0.01	-0.03 0.93 0.14	0.00 0.02 0.00	0.95 -0.02 -0.02	-0.37 0.79 0.12	-0.33 -0.05 0.05	0.57 -0.02 -0.01	-0.05 0.02 0.00
SURINAME	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.35 0.20 0.25	-0.08 -0.17 0.23	-0.23 -0.95 0.58	-0.13 -0.54 0.33	-0.01 -0.03 0.02	0.05 0.21 -0.13	-0.95 -3.88 2.36	0.00 0.01 0.00	-0.82 -3.36 2.04	0.04 0.15 -0.09	0.34 -3.38 0.65	-1.35 -1.89 -8.10	-0.32 0.73 0.04	0.47 4.28 20.42	0.06 0.10 0.18
SWEDEN	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.81 0.56 0.82 0.62	0.19 -0.35 -0.31 0.14	-0.13 0.22 0.23 -0.09	0.48 -0.83 -0.85 0.34	0.00 -0.01 -0.01 0.00	-0.16 0.27 0.28 -0.11	0.08 -0.14 -0.15 0.06	-0.03 0.05 0.05 -0.02	0.00 0.00 0.00 0.00	-0.41 0.70 0.72 -0.29	0.00 0.00 0.00 0.00	1.17 0.12 -1.06 -0.03	-0.14 -0.04 0.39 -0.19	0.02 0.07 1.14 0.01	0.51 0.20 0.39 2.07	0.00 0.01 -0.05 0.00
TRINIDAD AND TOBAGO	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp	0.59	-1.24	-0.07	-1.06	0.24	-0.27	0.15	0.22	-0.05	-0.68	0.08	0.09	0.22	0.02	0.00	0.02
dDp dep dr	0.30 0.37 0.21	-0.45 0.26 0.09	-0.02 0.02 0.01	-0.37 0.29 0.08	0.08 -0.07 -0.02	-0.09 0.07 0.02	0.05 -0.04 -0.01	0.08 -0.06 -0.02	-0.02 0.01 0.00	-0.24 0.18 0.05	0.03 -0.02 -0.01	0.43 1.15 0.45	0.24 -0.63 -0.13	0.02 -0.66 0.00	-0.46 0.37 -0.18	0.00 -0.15 0.01
UNITED KINGDOM	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	poil_1	gdps_1	Dps_1	eps_1	rs_1	dgdps_0	dDps_0	deps_0	drs_0
dgdp	0.71	0.57	-0.06	0.30	-0.09	-0.26	0.01	-0.01	-0.20	0.08	-0.25	0.97	0.24	-0.03	-1.01
dDp dep dr dpoil	0.68 0.66 0.28 0.36	-0.62 0.76 0.37 -1.68	0.07 -0.08 -0.04 0.19	-0.31 0.35 0.19 -0.87	0.10 -0.11 -0.06 0.26	0.27 -0.31 -0.17 0.75	-0.01 0.01 0.00 -0.02	0.01 -0.02 -0.01 0.04	0.21 -0.24 -0.13 0.58	-0.08 0.09 0.05 -0.23	0.26 -0.29 -0.16 0.73	0.18 -2.25 0.26 0.68	0.39 0.67 0.24 6.44	-0.02 0.74 0.00 -0.36	-0.01 -0.81 0.41 9.88
USA	R2	Intercept	gdp_1	Dp_1	r_1	Dps_1	eps_1	dDps_0	deps_0	dDps_1	deps_1	dgdp_1	dDp_1	dr_1
dgdp dDp dr	0.60 0.77 0.30	0.30 0.28 0.20	-0.03 -0.03 -0.02	-0.52 -0.53 -0.39	-0.09 -0.10 -0.07	-0.02 -0.02 -0.01	0.00 0.00 0.00	-0.15 -0.01 0.03	-0.04 -0.12 0.09	0.10 -0.03 0.09	0.02 -0.02 -0.15	0.45 0.15 0.16	-0.56 -0.17 -0.30	0.35 0.25 0.31

ANTIGUA AND BARBUDA	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.47 0.77 0.09	0.23 1.49 -0.07	0.00 0.03 0.00	-0.21 -1.32 0.06	-0.17 -1.04 0.05	-0.03 -0.18 0.01	0.02 0.12 -0.01	-0.01 -0.05 0.00	-0.10 -0.64 0.03	0.00 0.00 0.00	1.66 -0.26 -0.02	-0.16 0.09 0.03	-0.19 -0.12 -0.01	2.90 0.13 -0.14	-0.05 0.01 0.00
AUSTRIA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	eps_1	rs_1	dgdps_0	deps_0	drs_0
dgdp dDp dep dr	0.75 0.40 0.98 0.75	-0.71 -0.47 -0.90 -0.09	-0.28 -0.18 -0.35 -0.03	-0.35 -0.23 -0.44 -0.04	0.16 0.11 0.20 0.02	0.08 0.05 0.10 0.01	0.31 0.20 0.38 0.04	-0.17 -0.11 -0.22 -0.02	0.55 0.36 0.69 0.07	0.80 0.36 0.41 -0.02	-0.01 0.01 1.18 0.00	0.24 0.35 0.27 0.77
BAHAMAS	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.41 0.64 0.30	0.47 0.78 0.24	0.06 0.10 0.03	-0.36 -0.58 -0.18	-0.30 -0.49 -0.15	-0.07 -0.11 -0.03	0.24 0.38 0.12	-0.02 -0.02 -0.01	0.16 0.26 0.08	0.00 0.00 0.00	0.76 -0.25 -0.09	-1.01 0.96 0.01	0.03 -0.03 0.00	0.47 -0.21 0.08	0.04 -0.02 0.00
BARBADOS	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.50 0.53 0.71	-0.11 0.43 -0.04	-0.05 0.19 -0.02	0.17 -0.70 0.06	-0.51 2.07 -0.18	0.02 -0.09 0.01	-0.18 0.74 -0.06	0.00 -0.01 0.00	0.54 -2.19 0.19	0.01 -0.02 0.00	0.77 -0.16 0.01	1.00 0.50 -0.27	0.07 -0.15 -0.09	0.85 0.54 0.78	-0.03 0.03 0.01
BELGIUM	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.84 0.79 0.96 0.64	0.29 -0.57 0.30 -0.39	-0.31 0.61 -0.32 0.42	0.21 -0.42 0.22 -0.29	-0.03 0.06 -0.03 0.04	-0.04 0.08 -0.04 0.05	0.22 -0.43 0.22 -0.29	-0.11 0.22 -0.11 0.15	0.02 -0.05 0.02 -0.03	-0.03 0.05 -0.03 0.04	0.00 0.00 0.00 0.00	0.67 0.26 -0.04 0.21	0.16 0.70 0.14 0.48	-0.01 0.04 1.23 0.01	0.18 -0.30 0.19 0.48	0.00 0.01 0.01 -0.01
BELIZE	R2	Intercept	gdp_1	Dp_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dr	0.39 0.79 0.05	0.55 0.40 -0.03	0.14 0.11 -0.01	-0.97 -0.72 0.06	-0.15 -0.11 0.01	-0.08 -0.06 0.01	1.14 0.85 -0.07	0.09 0.07 -0.01	0.28 0.21 -0.02	0.02 0.01 0.00	0.92 0.18 -0.09	-0.12 0.83 -0.05	-0.03 0.12 -0.02	-1.23 -0.23 0.21	0.03 0.04 0.00
BULGARIA	R2	Intercept	gdp_1	Dp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep	0.87 0.20 0.09	-1.01 3.01 0.80	-0.06 0.19 0.04	0.03 -0.10 -0.02	-0.01 0.04 0.01	0.16 -0.49 -0.10	-0.48 1.48 0.29	0.18 -0.54 -0.11	-0.19 0.58 0.11	0.04 -0.13 -0.02	0.71 3.69 -8.00	-0.43 5.96 0.69	0.02 0.91 0.53	1.25 -12.30 12.36	0.02 0.23 -0.18
CAMEROON	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.69 0.12 0.64 0.12	0.95 0.05 -0.97 -0.10	0.10 0.00 -0.10 -0.01	-0.14 0.00 0.14 0.02	0.31 0.01 -0.31 -0.04	0.51 0.01 -0.51 -0.06	-0.18 -0.01 0.18 0.02	0.98 0.03 -1.00 -0.11	-0.35 -0.01 0.36 0.04	-0.96 -0.03 0.98 0.11	0.02 0.00 -0.02 0.00	0.55 -0.33 0.50 -0.23	0.51 0.18 -0.03 0.00	0.03 -0.05 1.40 0.01	-1.80 3.62 0.77 0.31	0.01 -0.06 0.01 0.00
CANADA	R2	Intercept	gdp_1	Dp_1	ep_1	r_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dDp dep dr	0.81 0.72 0.60 0.75	0.19 0.35 0.99 0.36	0.14 0.24 0.73 0.26	-0.33 -0.56 -1.68 -0.61	0.01 0.01 0.04 0.02	-0.16 -0.27 -0.80 -0.29	-0.14 -0.23 -0.70 -0.25	0.03 0.05 0.16 0.06	-0.03 -0.06 -0.17 -0.06	0.19 0.32 0.95 0.34	0.00 0.00 -0.01 0.00	0.94 -0.32 0.26 -0.04	0.28 0.48 -0.12 0.06	0.03 0.00 0.64 -0.03	-0.08 0.15 -1.40 0.71	0.01 0.00 -0.09 0.00
CHINA	R2	Intercept	gdp_1	ep_1	gdps_1	Dps_1	eps_1	rs_1	poil_1	dgdps_0	dDps_0	deps_0	drs_0	dpoil_0
dgdp dep	0.44 0.59	1.29 -7.75	0.11 -0.70	0.13 -0.83	-0.28 1.74	0.32 -2.04	0.02 -0.15	0.10 -0.66	0.02 -0.12	0.54 1.51	-1.17 -3.54	0.00 -0.82

Topics

Countries

Series

About

Resources

Abstract

I. Introduction

II. Stylized Facts

III. Methodology and Data

IV. Results

A. Oil price spillovers to ECCU countries.

B. The Potential Impact of an Expansionary Policy Stance in the U.S.

V. Conclusions and Policy Implications

References

Annex

List of countries included in the model