Dataset on the Total Value, Efficiency, and Driving Factors of Forest Ecological Products in Key State-Owned Forest Areas of Northeast China and Inner Mongolia, 2009–2023

Note that for some years, the “Total Value” column contains Excel sum formulas, indicating that the value was derived by aggregating the component values.Efficiency Measurement: Based on each forestry bureau’s inputs (such as forest land area, labor, and capital investment) and outputs (i.e., Gross Ecosystem Product), the Super-SBM method was used for calculation. Using the Malmquist index method, with adjacent two-year periods as one cycle, the total factor productivity (TFP) change index was calculated and further decomposed into technical progress (TC) and changes in technical efficiency (EC), with the latter subdivided into pure technical efficiency (PEC) and scale efficiency (SEC).

All indices use 2009 as the base year (base value = 1), and the values for subsequent years represent the cumulative multiple of change relative to the base year.Driver Analysis: The dataset includes eight natural, social, and policy variables: annual average temperature, annual average precipitation, forested area, vegetation cover (NDVI), forestry income levels, forestry industry structure, forestry labor productivity, and the level of central government financial compensation.

The driver data is stored separately by year. This dataset provides cross-sectional data for three key time points—2009, 2016, and 2023—to facilitate time-series comparisons and regression analysis for users.1. Worksheet “Total Value Results” (Index 1):Number of records: Includes specific value data for each forestry bureau across 15 years, annual aggregates for the “Total of 87 Forestry Bureaus,” and aggregated value data for the six major forestry industry groups.Row and column label definitions: Row labels are the names of forestry bureaus, arranged by forestry industry group.

Column labels are divided into 15 annual blocks; each block contains seven columns: year, total value, unit of measurement (100 million yuan), provisioning services, regulating services, supporting services, and cultural services. Some cells contain Excel sum formulas, indicating that the “Total Value” for that year is calculated by summing the first four service categories.2. “Efficiency Results” worksheet (Index 2):Number of records: Contains efficiency value records for 87 forestry bureaus, as well as summary rows for annual averages by forestry group and the overall population.Meaning of row and column labels: Row labels are also the names of the forestry bureaus.

Column labels are divided into two main sections: the left side shows the comprehensive efficiency values for each year from 2009 to 2023 (15 columns in total), and the right side shows the average efficiency values grouped by forestry group. All efficiency values are dimensionless efficiency indices.3. Worksheet “Index Decomposition Results” (Index 3):Number of records: Decomposition results for 14 consecutive-year intervals for each forestry bureau, plus summary averages by forestry group and for the overall population.Meaning of row and column labels: Row labels are the names of the forestry bureaus; column labels are the year intervals and decomposition indicators.4.

Worksheets “Driving Factors-2009,” “Driving Factors-2016,” and “Driving Factors-2023” (Indexes 4, 5, and 6):Number of records: Each worksheet contains values for 8 driving factors across 87 forestry bureaus.Meaning of row and column labels: Row labels are the names of forestry bureaus; column labels are annual average temperature (°C), annual average precipitation (mm), forested area (hectares), vegetation cover (NDVI, dimensionless, 0–1), forestry income level (yuan/person), forestry industrial structure (dimensionless, share of secondary industry), forestry labor productivity (10,000 yuan/person), and central government compensation level (yuan/mu).