BetterGov.ph
[IDEA] Open Source Agricultural machinery #411
Replies: 5 comments 1 reply
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https://www.facebook.com/share/v/17HNAQmMmZ/ example of how manual our farming is and why our neighbors out prodcur and export to us. https://youtube.com/shorts/nVzSZE5W5JY?si=pb9X68wc6Iiaonel |
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I sent an email to [email protected] offering our volunteering. Hope to be picked up. Bettergov is not just IT - engineers and makers - are a major part because physical logistics and material is a major part of how the Philippines can be better. |
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Slowly making Inroads and Trying to Connect to PUP ME student council - hope to get a positive response since we hope to donate machinery, PCs, and equipment and free FREECAD training. |
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Open source farming equip more developments The video discusses using open-source machines and methods to make housing more affordable and sustainable. Key points and metrics include: |
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Philippine Agriculture Productivity Indicators (1980–Present)Overview: The Philippines’ Agriculture, Forestry, and Fishing (AFF) sector has undergone significant changes since 1980. The AFF sector’s real output has grown over time, but its share in the economy has declined as the population and other sectors expanded. Below is a structured dataset of key indicators, followed by charts and observations on productivity trends. Key Indicators by Year (1980–2024)`
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| Year | AFF GVA (const. 2015 US$ billion) | Population (million) | AFF Employment (million) | AFF GVA per capita (US$) | AFF GVA per worker (US$) | AFF GVA per farm (US$) |
|---|---|---|---|---|---|---|
| 1980 | ~7.0 (est.) | 48.1 | n/a (≥50% of labor) | ~145 | n/a | n/a |
| 1985 | ~7.5 (est.) | 56.9 | n/a | ~132 | n/a | n/a |
| 1990 | ~8.0 (est.) | 65.3 | ~9.0 (≈45% of labor) | ~123 | ~890 | n/a |
| 1991 | ~8.2 (est.) | 66.8 | ~9.3 | ~123 | ~880 | 4.05k<sup>†</sup> |
| 1995 | ~9.5 (est.) | 73.1 | ~10.5 | ~130 | ~905 | n/a |
| 2000 | ~10.5 (est.) | 77.3 | ~10.4 (≈37% of labor) | ~136 | ~1,010 | n/a |
| 2002 | ~12.0 (est.) | 81.0 | ~11.0 | ~148 | ~1,090 | 4.8k<sup>‡</sup> |
| 2005 | ~15.0 (est.) | 87.2 | ~12.0 | ~172 | ~1,250 | n/a |
| 2010 | ~20.0 (est.) | 93.8 | ~11.9 (≈33% of labor) | ~213 | ~1,680 | n/a |
| 2012 | 29.7 (≈11% of GDP) | 97.4 | ~11.3 | 305 | ~2,630 | 5.3k[1] |
| 2015 | ~34.0 (est.) | 101.8 | ~10.9 | 334 | ~3,120 | n/a |
| 2020 | ~38.0 (est.) | 108.8 | ~10.7 (≈25% of labor) | 350 | ~3,550 | n/a |
| 2022 | ~40.5 (est.) | 113.9 | ~10.6 (≈22% of labor) | 356 | ~3,820 | 7.3k[1][2] |
| 2024 | 41.93 (latest) | 117.0 (est.) | ~10.5 (≈22% of labor) | 358 | ~3,990 | n/a |
†Estimated ~4.05k US$ per farm in 1991 (farmland ~9.97 Mha[3] at ~2.46 ha/holding).
‡Estimated ~4.8k US$ per farm in 2002 (no. of farms ~4.75 million, extrapolated).
Sources: AFF GVA 2012 and 2022 from PSA/World Bank data[4][5]; population from World Bank/PSA; farm counts for 2012 and 2022 from PSA’s Census of Agriculture[1] (1960 and 2022 figure: 2.17 million to 7.43 million farms)[2]. Employment shares from ILO/PSA (AFF employed ~45% of workforce in 1990s, falling to 22.37% in 2023[6][5]). (Entries labeled “est.” are approximate interpolations based on the above sources.)
Trends and Derived Indicators
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AFF GVA Growth: The real GVA of agriculture has increased dramatically from the early 1980s to today. In constant 2015 US$, the AFF sector’s output rose from only around $7–8 billion in 1980 to about $40+ billion in recent years (reaching $41.93 billion in 2024, the highest on record[4]). This reflects an over 5-fold increase in real agricultural output since 1980. However, agriculture’s share of GDP declined over the same period (from ~20–25% in the 1980s to only 9% of GDP by 2024[7]), as industry and services grew faster.
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Population vs. AFF Output: The Philippine population more than doubled from ~48 million in 1980 to about 114 million in 2022, exerting pressure on agricultural demand. Yet agricultural output per capita rose moderately (AFF GVA per capita increased from roughly $140 in 1980 to ~$350 in 2020). By 2022, AFF output per Filipino was about $356 in 2015 dollars (up from ~$213 in 2010), indicating some gains in per-capita food production. Still, agriculture’s per-capita contribution remains small, mirroring its shrinking GDP share.
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Employment in AFF: The number of workers in agriculture grew until the 1990s and then began to fall. In 1993, agriculture employed about 45.8% of all Filipino workers (the historical peak)[6]. Since then, labor has steadily shifted out of farming, dropping to just 22.5% of employment by 2022[6]. In absolute terms, agricultural employment hovered around 10–12 million people for decades. It likely peaked around 11–12 million in the 2000s and has since declined to roughly 10.6 million in 2022[8][9]. This outflow of labor, alongside modest output growth, has raised output per farmer over time.
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Farm Numbers and Size: According to decennial Census of Agriculture and Fisheries data, the number of farms/holdings expanded significantly – from about 2.17 million in 1960 to 3.42 million in 1980, 5.56 million in 2012, and 7.43 million in 2022[1][2]. This growth (over +240% since 1960) came even as total farmland area decreased by ~38% since 1991[3]. The average farm size consequently plummeted from ~3.6 ha in 1970 to just 0.83 ha in 2022[10]. AFF GVA per farm (a proxy for farm productivity) has improved – from roughly $2,000 per farm in 1960 to about $5,300 in 2012, and over $7,300 per farm in 2022 (in constant dollars). This indicates higher output per holding, although it partly reflects smaller farms and fewer farmers per holding.
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AFF GVA per Worker: Agricultural labor productivity (real GVA per worker) has markedly increased but remains low relative to other sectors. In 1990, a Filipino agricultural worker contributed on average under $1,000 of value a year, whereas by 2022 this had risen to roughly $3,800 per worker (constant 2015 US$). The improvement is due to labor shedding (fewer workers sharing the output) and modernizations in certain sub-sectors. However, one farm worker still produces far less economic value than a worker in industry or services, as shown below.
*Figure: Real GVA per Worker by Sector (constant 2015 US$). Agricultural productivity (yellow) has grown, especially as workers left farming, but it remains only a fraction of productivity in Industry (orange) and Services (pink). In 2023, agriculture engaged \~22% of workers but produced only \~9% of GDP[\[5\]](https://fr.theglobaleconomy.com/Philippines/value_added_agriculture_dollars/#:~:text=Forest%20area%2C%20percent%20%20,2022%20%20mm%20per%20year), underscoring a persistent productivity gap.*
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Sectoral Productivity Gap: The Industry and Services sectors have seen much higher output per worker. For example, industry (including manufacturing and construction) generated roughly $12,000–$15,000 per worker in recent years, while services generated around $8,000–$10,000 per worker, versus agriculture’s ~$3,000–$4,000[5]. This gap has widened over time. In the early 1990s, an average industrial worker was about 4–5 times as productive as an agricultural worker; today that ratio is on the order of 3–4 (and about 2–3 for services vs. agriculture). The shift of labor into higher-productivity sectors is one reason agriculture’s share of employment fell faster than its share of GDP. In short, agricultural productivity has improved, but lags far behind the productivity levels in industry and services, a major developmental challenge[5].
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Benchmarking vs. Industry/Services: In 1980, AFF contributed roughly a quarter of GDP and employed half the workforce; by 2020 it contributed <10% of GDP while employing ~25% of workers[7]. This indicates that output per worker in agriculture, though rising, is still only about one-third of the national average, whereas workers in industry and services produce above-average output. Government and international data (World Bank, PSA) consistently show agriculture as the least productive sector per job – a critical issue for rural incomes. Bridging this productivity gap through mechanization, better yields, and higher-value activities remains a policy priority.
Sources
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Philippine Statistics Authority – National Accounts and Statistical Yearbook data (various years) for GVA by sector and population.
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PSA – Census of Agriculture and Fisheries (1960, 1971, 1980, 1991, 2002, 2012, 2022) for farm counts and land area[3][1].
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World Bank – World Development Indicators for constant-price GVA and employment shares[4][5].
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International Labour Organization (ILOSTAT) – modeled estimates of employment by sector[6].
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Philippine Statistics Authority – Labor Force Survey results and PSA news releases for recent employment figures[8][9].
All data are publicly available via the PSA and World Bank. Figures for 2023–2024 are preliminary estimates. The overall trend is clear: the AFF sector’s productivity (output per worker and per farm) has improved over time, but it still trails the Industry and Services sectors by a large margin, reflecting structural changes in the Philippine economy[5].
[1] [3] [10] PHL farms increasing, but farm size shrinking–PSA | Ada Pelonia
https://businessmirror.com.ph/2025/01/01/phl-farms-increasing-but-farm-size-shrinking-psa/
[2] [PDF] The Philippines' Agrarian Reform: An Unfinished Business? - Zenodo
[4] [5] [7] Philippines Agriculture value added - données, graphique | TheGlobalEconomy.com
https://fr.theglobaleconomy.com/Philippines/value_added_agriculture_dollars/
[6] Employment in agriculture | Philippines – yearly data, chart and table
https://statbase.org/data/phl-employment-in-agriculture-share/
https://pidswebs.pids.gov.ph/CDN/document/1670816921\_6396a499d0052.pdf
Yes, your current graphs and dataset already support a tight core argument, and we can now frame your next layer of problem and comparison.
Here’s a breakdown of the key takeaways from your current material, the implied problem statement, and a scoped expansion into comparative data you asked for.
🟢 Part 1: What Your Current Graphs Already Prove
Based on the doc you shared, your analysis already demonstrates:
✅ A. Agricultural labor is declining
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AFF workforce dropped from ~45.8% (1993) to 22% (2022)
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Absolute worker numbers stagnated (~10–12 million), while farm counts rose (more small farms).
✅ B. AFF output per worker and per farm is improving
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Real GVA per worker grew ~4× from 1990 to 2022 ($880 → $3,820)
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GVA per farm doubled from ~$3.6k to ~$7.3k over 30 years
✅ C. But AFF’s share of GDP is declining
- From ~25% in 1980 to 9% in 2024
🔴 Part 2: What This Suggests (Emerging Hypothesis)
From this, it’s reasonable to infer:
“Yes, agriculture is getting more productive—but this is largely due to labor shedding, not total output transformation. And that likely means productivity gains are concentrated in fewer, more capitalized entities (or middle-scale farms).”
This links to industrialization and consolidation, even if not directly measured.
So yes, your hypothesis is fair:
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Productivity is up.
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Labor is down.
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Number of farms is up but size is shrinking.
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→ This hints at a split: many micro-farms + a few high-output producers.
🟡 Part 3: Framing the Core Problem Statement
Here’s a cleaned-up version of what you’re trying to articulate:
🔎 Problem Statement:
The cost of living in the Philippines—especially food—is rising faster than productivity improvements in agriculture. While output per farm and per worker has improved, it's not scaling fast enough to match population growth or regional peers. With a shrinking farm size base and rising input costs, the gap between food demand and efficient supply will widen unless we modernize smallholder production and close the regional productivity gap.
🔵 Part 4: What’s Missing – and What You Asked to Add
Here’s the exact comparative data that would now expand this meaningfully:
| Topic | Metric Needed | Country Scope |
|---|---|---|
| 🍚 Food affordability | Food CPI or cost of basic food basket vs income | PH vs. Vietnam, Thailand, Malaysia, Indonesia |
| 🌾 Productivity per farmer | GVA per agri worker, constant prices | Same |
| 🌍 Output vs Population | Agriculture output per capita | Same |
| 🧺 Share of food in household spend | % of income spent on food (Engel coefficient) | Same |
| 💵 Price benchmarking | Cost per kg of rice, meat, veg, etc. (average) | Same |
✅ Your Next Move (Options)
Option 1: Kick off deep research
I can start now on:
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Per-farmer GVA comparison (PH vs. ASEAN-5)
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Food price benchmarks
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Food expenditure share by country
Let me know if you want this in:
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Spreadsheet
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Chart-ready format
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FB/Viber-post narrative
Option 2: Want a "One-Pager" Summary?
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Special Area for Agricultural Development Annual Report 2024Simplified Problem Statements and Challenges for DOA/SAAD OperationsBelow is the simplified, structured version of the challenges you outlined. These follow a clear Internal vs External categorization for operations analysis. I. INTERNAL CHALLENGES (DOA / SAAD Operations)Internal = Everything inside DOA operations (people, tools, systems, logistics, policies). If these fail, external outcomes to farmers cannot be delivered. 1. Logistics of PR and Support for Beneficiaries
Core Need: Strengthen logistics, improve communication loops, unify channels of information. 2. COS Workforce Stability, Pay, and Tools
Core Need: Stabilize the workforce, improve compensation, and equip personnel properly. 3. Stronger Policy Framework + Process Standardization + Workforce Training
Core Need: Consistent processes, shared tools, unified training, and a trained/stable workforce. 4. Time-Bound Program (Until 2028) → Pressure for Rapid Capacity Building
Core Need: Accelerated capability-building and efficient operational scaling. 5. Data Integration and Accuracy Problems
Core Need: Reliable data systems, continuous data cleaning, and better integration. 6. Expansion of Coverage While Maintaining Precision in Targeting
Core Need: More manpower, more funding, better tools, and improved targeting systems. 7. Procurement and Delivery Bottlenecks
Core Need: Faster procurement cycles, improved vendor management, and streamlined processes. 8. Need for Stronger Communications & PR Infrastructure
Core Need: Professional, stable, well-equipped communications structure across all regions. II. EXTERNAL CHALLENGES (Farmers & Communities)External = Outcomes delivered to farmers. These depend entirely on internal DOA capacity. 1. Logistical & Operational Barriers in Reaching Farmers
Impact: Farmers receive delayed or incomplete support. 2. Weak Enterprise Development & Market Linkages
Impact: Even when farmers receive inputs, they cannot grow into sustainable enterprises. 3. Resource Deployment & Manpower Constraints Affect Outcomes
Impact: The effectiveness of the entire program is reduced. III. Core Synthesis / One-Line Executive SummaryThe effectiveness of DOA depends on fixing internal operations first—logistics, procurement, pay, workforce stability, policies, processes, data, and communications. Without these, farmers will not receive consistent, timely, high-quality support, and enterprise development cannot take root. If you want, I can turn this into:
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Vision
Empower local workshops, schools, and farmers to build and maintain essential agricultural equipment through open-source designs. The aim is to lower CAPEX and maintenance costs, create skilled jobs, and strengthen food security by developing highly repairable, transparent, and standardized tools — starting with the Open Source Micro Tractor.
Concept Example: The Open Source Micro Tractor
Background
Traditional Filipino farming relies heavily on the carabao (water buffalo) for land preparation. However, a carabao can plow only 0.25 to 0.5 hectares per day depending on soil conditions and terrain.
By contrast, a Micro Tractor (1–2 kW power output) can till 1 to 1.5 hectares per day, depending on soil hardness and moisture levels. This increases productivity by roughly 3x to 5x while reducing labor fatigue and animal maintenance costs.
Cost Comparison
How It Will Work
1. Expert Participation and Engineering Analysis
2. Sourcing and Transparency through BetterGov.ph
3. Building and Replication Model
Budget and Phasing
Sustainability Plan:
Maintain a Technological Division to continuously develop, test, and improve open-source agricultural machinery. As industrialization advances, this division can expand into renewable energy, aquaculture, and post-harvest processing technologies.
Expected Impact
References
Summary Statement:
BetterGov.ph can serve as the national transparency and accountability hub for open-source industrialization — tracking every peso, partner, and project milestone in real time, while ensuring that all designs and data remain free and accessible to the public.
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