
==== Front
Data Brief
Data Brief
Data in Brief
2352-3409
Elsevier

S2352-3409(24)00766-2
10.1016/j.dib.2024.110802
110802
Data Article
IMF WEO macroeconomic forecasts panel dataset
Ech-charfi Nour-eddine nour-eddine.ech-charfi@um6p.ma
@NordiEchcharfi

Africa Business School, Mohammed VI Polytechnic University (UM6P), Campus Rocade, Rabat 11103, Morocco
09 8 2024
10 2024
09 8 2024
56 1108024 6 2024
29 7 2024
31 7 2024
© 2024 The Author(s)
2024
https://creativecommons.org/licenses/by-nc/4.0/ This is an open access article under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
This paper introduces a meticulously organized dataset derived from the International Monetary Fund's World Economic Outlook (IMF WEO) forecasts, including GDP growth, CPI inflation, and current account balances for 196 countries from 1990 to 2024. Sourced from the WEO historical database and updated to 2024, the dataset contains forecasts of crucial economic indicators — GDP growth, CPI inflation, and current account balance — in an accessible and user-friendly Excel format. This dataset is a valuable resource for academic researchers, economists at central banks, finance ministries, and other stakeholders, enabling diverse analyses such as evaluations of IMF forecasts, research into optimism bias, and studies on equilibrium exchange rates. Additionally, it may be useful for foreign investors in making informed strategic investment decisions.

Keywords

IMF
WEO
Economic forecasts
Tidy dataset
GDP growth
CPI inflation
Current account balance
==== Body
pmcSpecifications TableSubject	Macroeconomics	
Specific subject area	IMF WEO Forecasting	
Type of data	Table (Excel Format); Excel (.xlsx)	
Data collection	Hand-collected from the IMF website and converted into a tidy, user-friendly format	
Data source location	All raw data are downloaded from the International Monetary Fund (IMF) World Economic Outlook (WEO) database.	
Data accessibility	Repository name: Mendeley Data
Data identification number: 10.17632/8dt6xpp6×4.6
Direct URL to data:
https://data.mendeley.com/datasets/8dt6xpp6x4/6	
Related research article	None	

1 Value of the Data

• This dataset can serve academic researchers, economists at central banks, and finance ministries, among others, in their various analyses.

• One practical application of this dataset is to compare a country's forecasted GDP growth with regional and income group averages.

• The dataset allows for the assessment of IMF forecasting performance. The IMF and academic researchers have conducted a series of evaluations of WEO macroeconomic forecasts [[1], [2], [3], [4], [5]]. In addition, a substantial body of literature examines the “optimism bias” in IMF forecasts [[6], [7], [8]]. Most studies on IMF forecast bias use regional data for developing countries, not country-specific data. One exception, however, is Dreher et al. [3]. This dataset will allow researchers to explore forecast bias using country-specific data. It will also allow the assessment of WEO forecasts for different horizons.

• Central banks can use this dataset to assess the medium-term evolution of the real exchange rate. GDP growth and inflation rates are two fundamental variables that drive equilibrium exchange rates in medium- and long-run. Economists at central banks may use this dataset to compute predicted GDP growth and inflation for different horizons.

• Foreign investors may rely on this dataset to make strategic investment decisions, especially in countries with limited reliable alternative sources. Faster-growing countries attract more foreign investment and may signal positive investor sentiment, potentially leading to exchange rate appreciation.

2 Background

The IMF regularly produces forecasts of macroeconomic variables for a large number of economies around the world. The Fund publishes these projections twice a year (in April and October) as part of its World Economic Outlook (WEO) reports. The IMF relies primarily on information gathered by its country desk officers in the context of their missions to IMF member countries and through their ongoing analysis of the evolving situation in each country.

I arrange the WEO historical data into a “tidy” format, where variables are in columns, and each observation corresponds to a row [9], and updated it until April 2024.1 For every country c and every year t, the dataset contains WEO projections fc,t,h for horizons spanning from the current year t to t+5. These forecasts are released biannually, in April and October. I supplement the dataset with two attributes for each country: (i) geographic region and (ii) income group. Moreover, I add the realization values of GDP growth, inflation, and current account balance into the dataset.

3 Data Description

I draw from the publicly available IMF historical forecast dataset. This dataset includes, for each WEO exercise (Spring and Fall), the IMF forecast of three economic variables (GDP growth, CPI inflation, Current account as% of GDP) for the same year and the forecast for each of the following five years. The WEO historical database is in the “wide” format, with countries in rows and WEO-year-exercise in columns, making it difficult to use in empirical analyses.

To prepare my dataset, I first convert the dataset from a “wide” to a “long” format using the tidyr package in R. I then break down the columns were into three variables: year, WEO exercise, and horizon. Next, I merge the three forecasted variables (GDP growth, CPI inflation, and current account balance as% of GDP) a single dataset. The dataset was subsequently updated with realization values for each variable using the latest WEO data. Finally, geographic region and income group attributes were added to the dataset.

The main Excel spreadsheet includes eight variables detailing each countryʼs attributes, alongside three key variables and their actual values. Table 1 below describes each variable in the dataset.Table 1 Data description.

Table 1:Variable	Description	
Country	The country's name	
CCode	Country and Area Codes	
WEO_year	The publication year of the WEO	
region	The country's regional grouping	
incomegroup	The country's income group	
year	the year of forecast	
exercise	WEO exercise (April or October)	
h	The horizon (1,2,3,4, 5 and 6), where h = 1 is the forecast for the same year.	
ngdp_rpch	(Forecast) GDP growth (Annual percent change)	
pcpi_pch	(Forecast) CPI inflation Inflation rate, average consumer prices (Annual percent change)	
bca_gdp	(Forecast) Current account balances (% of GDP)	
Rngdp_rpc	(Realized) GDP growth (Annual percent change)	
Rpcpi_pch	(Realized) CPI inflation Inflation rate, average consumer prices (Annual percent change)	
Rbca_gdp	(Realized) Current account balances (% of GDP)	

Table 2 provides an example of WEO Fall 2014 forecasts compared to actual values for the same year and the following five years (2015–2019) for four groups of economies. Global economic growth forecasts, including those for EMDEs, are overly optimistic for horizons beyond the current year. Conversely, Euro area GDP growth forecasts are consistently pessimistic over five horizons. This may reflect the IMF's pessimism following the Eurozone crisis (2010–2012). The 2014 WEO inflation forecasts were overall pessimistic in that they consistently overshoot inflation rates for different horizons.Table 2 Forecasts and outturns of growth, inflation, and current account balance (WEO Fall 2014).

Table 2:	H = 1	H = 2	H = 3	H = 4	H = 5	H = 6	
	[F]	[O]	[F]	[O]	[F]	[O]	[F]	[O]	[F]	[O]	[F]	[O]	
Growth:	
World	3.31	3.6	3.85	3.5	4.04	3.3	4.07	3.8	4.05	3.6	4.05	2.8	
		(−0.29)		(0.35)		(0.74)		(0.27)		(0.45)		(1.25)	
AE	1.83	2.1	2.35	2.4	2.43	1.8	2.41	2.6	2.31	2.3	2.26	1.8	
		(−0.27)		(−0.05)		(0.63)		(−0.19)		(0.01)		(0.46)	
EMDE	4.43	4.7	4.95	4.3	5.19	4.4	5.23	4.8	5.22	4.7	5.23	3.6	
		(−1.27)		(0.65)		(0.79)		(0.43)		(0.52)		(1.67)	
Euro area	0.83	1.4	1.35	2	1.70	1.9	1.71	2.6	1.64	1.8	1.63	1.6	
		(−0.57)		(−0.65)		(−0.2)		(−0.89)		(−0.16)		(0.03)	
CPI inflation:	
World	3.80	3.2	3.92	2.7	3.84	2.7	3.68	3.3	3.63	3.6	3.57	3.5	
		(0.6)		(1.22)		(1.14)		(0.38)		(0.03)		(0.07)	
AE	1.57	1.4	1.77	0.3	1.95	0.7	1.95	1.7	1.97	2	1.94	1.4	
		(0.17)		(1.47)		(1.25)		(0.25)		(−0.03)		(0.54)	
EMDE	5.55	4.7	5.56	4.7	5.24	4.4	4.93	4.5	4.78	5	4.68	5.1	
		(0.85)		(0.86)		(0.84)		(0.43)		(−0.22)		(−0.42)	
Euro area	0.54	0.4	0.92	0.2	1.23	0.2	1.36	1.5	1.46	1.8	1.52	1.2	
		(0.14)		(0.72)		(1.03)		(−0.14)		(−0.34)		(0.32)	
Current account balance (% of GDP):	
AE	0.27	0.5	0.19	0.6	0.15	0.8	0.10	1	0.118	0.8	0.164	0.8	
		(−0.23)		(−0.41)		(−0.65)		(−0.90)		(−0.68)		(−0.64)	
EMDE	0.753	0.5	0.541	−0.3	0.489	−0.4	0.446	−0.1	0.365	−0.2	0.378	0	
		(0.25)		(0.84)		(0.90)		(0.55)		(0.56)		(0.378)	
Euro area	1.96	2.3	1.95	2.6	1.92	3	1.84	3.1	1.86	2.8	1.84	2.4	
		(−0.34)		(−0.65)		(−1.08)		(−1.26)		(−0.94)		(−0.56)	
Note: The table presents the IMF Fall WEO forecasts [F] and actual outcomes [O] for three variables across major groups of economies for the current year (2014, h = 1) and the following five years (2015 [h = 2] to 2019 [h = 6]).

Forecast errors are in parentheses (e≡ϝ−R).

AE: Advanced economies; EMDE: Emerging Markets and Developing Economies.

Table 3 presents summary statistics for 1990–2024, covering both cross-sectional and time dimensions. It displays GDP growth forecast errors for each forecast horizon. These forecast errors are negative for h = 1 but consistently positive for other horizons, indicating an optimistic bias in IMF GDP growth forecasts.Table 3 Summary statistics: 1990–2024.

Table 3:Variable	N	n	Mean	Overall std. dev.	Between std. dev.	Within std. dev.	Min	Max	
			Realization				
Full Sample:									
Rngdp_rpc	6351	196	3.40	6.55	2.06	6.24	−54.3	148	
Rpcpi_pch	6298	196	41.20	933.87	209.53	908.86	−72.7	65,374.1	
Rbca_gdp	6121	195	−2.15	13.76	9.21	10.84	−242.2	314.9	
OECDCountres:								
Rngdp_rpc	1065	38	2.37	3.13	1.19	2.93	−11.9	24.5	
Rpcpi_pch	1065	38	4.22	9.01	5.80	6.49	−1.7	104.5	
Rbca_gdp	1061	38	0.31	5.08	3.83	3.27	−22.7	30.2	
									
Non-OECDCountres:							
Rngdp_rpc	5286	170	3.61	7.02	2.17	6.70	−54.3	148	
Rpcpi_pch	5233	170	48.73	1024.34	224.62	997.06	−72.7	65,374.1	
Rbca_gdp	5060	169	−2.67	14.90	9.71	11.81	−242.2	314.9	
			Errors, GDP Growth, H = 1				
Full Sample	6143	196	−0.27	4.54	1.00	4.43	−89.21	94.87	
OECD	1061	38	−0.40	1.46	0.48	1.39	−19.65	6.79	
Non-OECD	5082	170	−0.25	4.94	1.07	4.83	−89.21	94.87	
			Errors, GDP Growth, H = 2				
Full Sample	6140	196	0.77	5.82	1.92	5.58	−130.69	71.92	
OECD	1061	38	0.32	2.66	0.70	2.58	−21.45	13.50	
Non-OECD	5079	170	0.87	6.28	2.04	6.02	−130.69	71.93	
			Errors, GDP Growth, H = 3				
Full Sample	6136	196	0.98	5.98	1.78	5.76	−143.58	63.24	
OECD	1061	38	0.60	2.89	0.71	2.81	−22.02	13.05	
Non-OECD	5075	170	1.06	6.43	1.90	6.20	−143.58	63.24	
			Errors, GDP Growth, H = 4				
Full Sample	6134	196	1.06	5.75	1.71	5.52	−143.58	59.62	
OECD	1061	38	0.69	2.91	0.94	2.81	−21.66	13.1	
Non-OECD	5073	170	1.14	6.18	1.82	5.93	−143.58	59.62	
			Errors, GDP Growth, H = 5				
Full Sample	6134	196	1.11	5.89	1.68	5.64	−143.58	57.13	
OECD	1061	38	0.71	2.89	0.96	2.79	−21.20	12.97	
Non-OECD	5073	170	1.19	6.33	1.78	6.07	−143.58	57.13	
			Errors, GDP Growth, H = 6				
Full Sample	6134	196	1.15	5.82	1.74	5.58	−146.38	61.74	
OECD	1060	38	0.78	2.84	0.93	2.74	−21.01	12.98	
Non-OECD	5074	170	1.22	6.27	1.85	6.00	−146.38	61.74	
Note: N denotes the number of observations, n is the number of countries, and mean is the overall average. The standard deviation (std. dev.) is split into three components: overall, between (variation across countries), and within (variation within each country over time). Min and Max indicate the minimum and maximum values.

Fig. 1 shows the missing data map for the dataset, where 5 % of the data is missing and 95 % is observed. This indicates that missing data is relatively minimal in this dataset.Fig. 1 Missing data map. Note: The missing data map for the dataset shows 5 % missing values (in red) and 95 % observed values (in navy blue). Variables (in the x-axis) are ranked by the amount of missing data.

Fig. 1:

Figure 2 depicts distribution of forecast errors for GDP growth. For each country i during year t, I define eit≡ϝit−Rit, where e represents forecast error, ϝ denotes the forecast, and R denotes its respective realization. Short-term GDP growth forecasts are relatively accurate and show little bias. However, two — to five-year-ahead WEO growth forecasts tend to be upward biased, with median errors (red vertical line) increasing with forecast horizons (h).Fig. 2 Distribution of GDP growth Forecast Errors, by horizon. Note: Moving from top to bottom along the vertical axis of each chart, I show the distribution of GDP growth forecast errors in increasing order of length of the forecast horizon, namely the current-year Fall (h = 1), next-year Fall (h = 2), followed by the two-, three-, four-, and five-year Fall WEO forecasts (h = 3 to h = 6). The median forecast errors (the vertical red line) increase with the forecast horizon h.

Fig. 2:

4 Experimental Design, Materials and Methods

IMF WEO forecasts are not purely mechanical outputs from econometric models as they incorporate expert judgments based on gathered information. Here, I briefly explain the process of producing these forecasts within the IMF, describe the variables, and summarize the data.

Table 4 shows the timeline of IMF WEO forecasts, with the WEO fall (published in October) providing yearly forecasts for five years, including the current year (t). For example, the October 2024 WEO publishes forecasts for 2024 (h = 1) and includes yearly forecasts for 2025–2029 (h = 2 to h = 6).Table 4 IMF WEO forecast horizons.

Table 4:Image, table 4	

The WEO forecasting cycle requires between three and four months. IEO [10] and Genberg et al. [2] detail the IMF WEO's forecasting process. Fig. 3 shows the information flow during a typical WEO forecast cycle. The IMFʼs process for producing WEO forecasts begins the “initial conditions meeting.” The economic modeling division (EMD) chairs this meeting to gather initial conditions needed for forecasts using the global projection model (GPM).2Fig. 3 The IMF's process for producing WEO forecasts Note: Black lines represent flows of information that serve as inputs at various stages of the process. Blue lines represent the flow of forecast information produced by EMD with GPM. Red lines represent the flow of WEO forecasts. Each line segment is coded with a letter from A to O, whose meaning is explained in the text.

Fig. 3:Source: Genberg et al. [2, p.5]. (For interpretation of the references to color in this figure legend, the reader is referred to the web version of this article.)

The discussions within the inter-departmental forecast committee (IDFC) produce a set of initial global conditions transmitted by the WEO coordination team to each country desk economist. The research department (RES) provides additional information in consultations with country desks and area departments (arrow B). This supplements data gathered in the initial conditions meeting and helps initialize the GPM (arrow C).

The EMD releases GPM forecasts to world economic studies (WES) studies (arrow D). WES combines these forecasts with global conditions, such as commodity prices, fiscal policy developments in large economies, and interest rate trends, into a “global assumptions memo” for departments and country desks to begin the WEO round (arrow E). The GPM forecasts are also sent to the meeting on surveillance issues (arrows J and L) for feedback on critical assumptions.

IMF forecasts, prepared by country economists, originate at the country desk (arrow F). IMF forecasts by country economists start at the country desk (red arrow G). The two-sided arrow indicates coordination between country desks and area departments to ensure coherent forecasts. The arrow H represents the coordination between country desks, departments, and WES to ensure that WEO forecasts are coherent when aggregated for global forecasts.

The process of WEO forecasts is an iterative process, starting and ending with country desks but involving reviews and consistency checks by departments and WES (arrows G and H). These checks ensure that forecasts are coherent from both regional and global perspectives.

Finally, the WEO is typically released three days before the international monetary and financial committee (IMFC) meeting, at a press conference by the economic counselor (arraw O). This step is the most publicized, as the IMF broadcasts the press conference live online.

Limitations

Not applicable.

Ethics Statement

I confirm that I adhere to Data in Brief's ethical requirements and that this work does not involve human subjects, animal experiments, or social media data.

CRediT Author Statement

I am the only writer of this paper.

Data Availability

IMF WEO Macroeconomic Forecasts Panel Dataset (Original data) (Mendeley Data).

Acknowledgments

This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.

Declaration of Competing Interest

I affirm that there are no known competing financial interests or personal relationships that could have influenced the work reported in this paper.

1 The Historical WEO Forecasts Database is publicly available here: https://www.imf.org/-/media/Files/Publications/WEO/WEO-Database/WEOhistorical.ashx

2 In the meeting, representatives from key country desks and regional departments provide updates on new policy initiatives and events affecting economic conditions. The RESʼs commodities unit provides projections of future commodity prices, the financial affairs department (FAD) updates on fiscal policy developments, and the monetary and capital markets department (MCM) provides information on interest rates and financial market conditions.
==== Refs
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