Tourism Value Added Dataset by Country, Sector and Year (1995–2020)

Description

The dataset provides tourism value-added indicators broken down by country, sector, and year for the period 1995–2020. It includes the direct, indirect, and total value added generated by inbound tourism expenditure, along with unit value-added measures calculated per unit of inbound tourism spending. These indicators are constructed within a multiregional input–output (MRIO) framework, which enables the quantification of both the direct effects and the indirect, upstream supply‑chain impacts associated with inbound tourism demand. The dataset is constructed using the OECD Inter-Country Input–Output (ICIO) tables. (OECD, 2023). Inbound tourism demand is connected to sectoral output through input–output linkages, enabling the estimation of value added generated along global production networks. Dataset Specifications • Coverage: 77 economies (including a "Rest of the World" aggregate) following OECD ICIO framework. • Sectoral Classification: 45 sectors following the OECD ICIO classifications. • Temporal Scope: Annual time series (1995–2020), facilitating longitudinal analysis of structural economic shifts. • Key Metrics: Quantifies direct, indirect, total, and unit tourism value added, capturing both immediate and supply-chain impacts. Repository files: • tourism_value_added_mrio_panel_1995_2020.csv — Main panel dataset (country × sector × year) • README.txt — Detailed documentation on methodology, variable definitions, and usage notes • country_codes.csv — Codebook with country identifiers and names • sector_codes.csv — Codebook with sector codes and descriptions

Steps to reproduce

1. Data acquisition Download the OECD Inter-Country Input–Output (ICIO) tables (2023 edition) from the OECD database. From this database, extract the global input–output matrices, the final demand matrices, and the value-added vectors for all available years in the period 1995–2020. 2. Extraction of tourism demand Identify inbound tourism demand using non-resident household final consumption expenditure. Derive bilateral tourism-related final demand flows and subsequently aggregate these flows at the destination-country level. 3. Sectoral mapping Map tourism demand to the 45-sector ICIO classification for each country, ensuring consistency between demand vectors and the input–output structure. 4. Construction of technical coefficients Compute the matrix of technical coefficients from the ICIO tables and derive the Leontief inverse matrix. 5. Estimation of value added Calculate sectoral value-added coefficients (value added per unit of output). Direct value added is obtained by multiplying the diagonal matrix constructed from the value-added coefficient vector with the tourism final demand vector. Total value added is computed by multiplying the diagonal matrix constructed from the value‑added coefficient vector with the Leontief inverse and subsequently multiplying the resulting matrix by the tourism final demand vector. Indirect value added is then derived as the difference between total and direct value added. 6. Computation of unit value added Unit value-added indicators are not obtained by dividing sectoral value added by aggregate tourism expenditure ex post. Instead, for each country–year observation, the sectoral tourism demand vector is normalised such that the aggregate inbound tourism demand sums to unity. The MRIO model is then re-applied to this normalised country-specific demand vector. This yields direct, indirect, and total value added per unit of inbound tourism demand for each sector. 7. Panel construction Integrate the observations from all countries, sectors, and years (1995–2020) into a harmonized panel dataset. 8. Output files Export the final dataset in CSV format and generate accompanying codebooks for country and sector classifications.

Institutions

• Hellenic Mediterranean University

  Crete, Heraklion

Categories

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