IEEM+ESM APPLICATION
Papua New Guinea
Building a forest products industry and the livelihoods that come with it, in a country whose forest is still standing. Run the integrated green growth package and see what it takes.
Seven interventions, solved together to 2060.
Stage 1. The economy
US$59.7 billion of output, bought with US$28.3 billion of public borrowing.
Real gross domestic product, difference from the baseline
Source: Open IEEM Platform, results set PARITY_20260901.
Note: real gross domestic product at factor cost, annual difference from the no-shock baseline, per cent. All ecosystem service channels active.
And what it costs
US$1.26 billion of mill capacity. US$3.8 billion to establish the plantation estate and US$3.0 billion to replant it, all paid inside the period. Government foreign debt at 2060 stands US$28.3 billion above the baseline, the borrowed half of the build and of the other programs.
The largest single part of the output gain, the end of illegal logging and deforestation, is bought with US$44.1 billion of carbon payments from abroad over 2027 to 2060. That result is conditional on that finance.
Government revenue at 2060 is 16.6 percent lower in nominal terms. With the government balance held, the carbon revenue and the foreign financing let the direct tax rate fall to 0.59 of its baseline level.
Stage 2. The land
3,249,000 hectares of forest still standing at 2060 that the baseline does not have.
Source: Open IEEM Platform, results set PARITY_20260901.
Note: forest area at 2060, hectares against the baseline. The rows below the package are each policy solved on its own. Forest area is close to additive across the land policies; the economic effects are not, because the policies compete for the same labor and the same timber.
Tap the map to enlarge it.
The estate’s harvest is 8 to 9.6 million cubic meters a year in its thinning years from 2037 and 35 million a year in its harvest years from 2049. The national cut in 2023 was 4.6 million.
Stage 3. What the forest does
Small, and that is the point: the forest is still there, so the services are already in the baseline.
Together these are worth 0.05 percentage points of gross domestic product at 2060, against a total policy effect of 5.83. Only the change in a service reaches the economy. In a country that has already lost most of its forest, the same platform produces the opposite result.
Where each service is heading, against its own starting level
Source: Open IEEM Platform, results set PARITY_20260901.
Note: each service indexed to its own 2026 level, except particulate removal which is indexed to 2030. Sediment export and nitrogen export are quantities where a lower line is a better outcome; pollinator abundance and particulate removal are quantities where a higher line is better. The dotted lines show what happens if the forest goes.
Tap the map to enlarge it.
Source: Open IEEM Platform, results set PARITY_20260901.
Note: additional fine particulates removed by vegetation under the package, year by year to 2060. The pollution surface is held fixed at its base year throughout, so the animation shows the effect of changing vegetation rather than of changing pollution. Service gains cluster where the avoided clearing is: the highland fringe and the Sepik and Gulf lowlands. The same hectares carry more than one service, which is where conservation spending goes furthest.
Coastal protection is quantified and reported but not credited to the program. Existing mangroves prevent US$10.0 million of expected coastal property damage a year. No policy in this study changes mangrove extent, so including it would credit the program with the value of habitat that does not change.
Stage 4. Building the industry
Built on their own the mills earn nothing at all. Built with the export restriction the sector grows 327.8 percent.
| At 2060 | Restrict log exports, alone | Build the mills, alone | Both together |
|---|---|---|---|
| Mill output | +10.0% | +41.2% | +327.8% |
| Logs taken by the mills | +10.0% | +312.5% | +1,150.3% |
| Processed wood exports, against the baseline | 7.6 times | 36.7 times | 274 times |
| Mills’ return on capital, against the economy average | 1.40 | 0.00 | 0.16 |
Source: Open IEEM Platform, results set PARITY_20260901.
Note: percentage differences from the baseline unless stated. Ratios are the scenario value divided by the baseline value. The return on capital is the mills’ return relative to the economy average.
The restriction cuts the log price by 17.2 percent, but the mills that already exist cannot use cheap logs: logs are only 16.1 percent of what they spend. New mills can, because logs are 47 percent of theirs. Built on their own, into an unrestricted log market, those mills earn nothing at all. Each instrument supplies exactly what the other lacks, and neither is worth doing without the other. That is the case for industrial policy, and it is not an argument from principle. It is what the model produces.
What gets built
Raw log exports reach zero in 2049. By 2060 the country exports 2.26 million cubic meters of processed wood, against 61 thousand cubic meters exported in 2023. Logging output is 44.7 percent above the baseline: the restriction redirects the cut rather than ending it, and the plantation estate is what makes that supply sustainable.
The livelihoods
The unemployment rate at 2060 is 1.4 percentage points above the baseline. In this model that measures labor released from the activities that contract, chiefly export tree crops, rather than job loss as a labor statistician would measure it.
Stage 5. Wealth, and the report
The package adds more to what the country owns than to what it produces.
Source: Open IEEM Platform, results set PARITY_20260901.
Note: genuine savings, the change in national wealth per year, cumulated over 2027 to 2060, on the reading that includes the emission terms at US$30 per tonne of carbon dioxide.
The plantation makes the point on its own: it costs US$5.5 billion of gross domestic product inside the period and adds US$18.5 billion of wealth, because the estate is standing forest and carbon before it is timber, and the timber it will supply after 2060 is not counted here at all.
The question
Can Papua New Guinea build a forest products industry and the rural livelihoods that come with it, without spending the natural capital the industry depends on?
What the platform found
It can, and not by leaving it to the market. The instruments that build the industry are worth almost nothing apart. Together they raise processed wood exports to 274 times their 2023 level, end raw log exports by 2049, and multiply employment in the mills three and a half times. Real household consumption per head is 6.3 percent higher at 2060 and 3,249,000 hectares more forest is standing.
What it means for public finance
The industry does not build itself: the mills built into an unrestricted log market earn nothing. The case for public investment rests on what conventional appraisal leaves out, which is the wealth the standing forest and the growing estate represent. On output the package returns US$59.7 billion. On national wealth it returns US$77.9 billion. Discounted at 12 percent, the package’s gain is 0.97 percent of the discounted baseline path, against 0.85 for avoided deforestation on its own.
What the analysis rests on
A recursive dynamic economy-wide model of Papua New Guinea, coupled to a spatially explicit land use model and to biophysical models of erosion mitigation, crop pollination, water purification, air filtration, flood mitigation, coastal protection, climate regulation and water regulation. Five services are transmitted to the economy. Every result is the difference the model produces between the scenario and the baseline under the assumptions stated in the paper and is conditional on them.