Productive Capabilities and Trade Agreements Database (PCTAD): A Panel Dataset of Bilateral Trade Relations, 2011-201

This dataset provides a comprehensive framework for analyzing the relationship between productive capabilities and trade agreement formation across 95 countries from 2011 to 2017. It combines bilateral trade agreement status, productive capability measures, and sectoral productivity differentials for 8,575 unique country pairs, creating a novel resource for studying economic development and trade integration.
The database merges information from multiple authoritative sources: trade agreement indicators from the CEPII Gravity database, maritime distances from CERDI-SeaDistance, productive capability measures from UNCTAD's Productive Capabilities Index (PCI), and sectoral productivity differentials from the RPROD database. Each observation represents a bilateral country relationship in a given year, with detailed information on trade agreement status, economic capabilities, geographic distance, and productivity measures.
Key variables include:

-Binary indicators for active trade agreements
-Productive Capability Index (PCI) for both origin and destination countries
-Balassa-Samuelson effect measures capturing sectoral productivity differentials
-Bilateral maritime distances and connectivity measures
-Trade flow values and related economic indicators

This unified dataset is particularly valuable for researchers studying:

-Trade agreement formation and economic development
-Productive capability thresholds in international trade
-Regional patterns in economic integration
-Development policy and trade liberalization sequencing

The data structure allows for both cross-sectional and longitudinal analyses, providing a rich foundation for investigating how domestic economic capabilities influence international trade relations. The time period (2011-2017) represents a relatively stable era in international trade, making it ideal for studying structural relationships without the confounding effects of major global disruptions.