Development Impact Statement

Part one: what this statement is for

Structure. Each part has one job. Part 1 is the problem, Part 2 is the route home, Part 3 is the change, Part 4 is the proof.

Word plan.

Do not repeat yourself between parts. The most common structural failure is saying the same thing in Parts 1, 2 and 3. Each part should add something the others do not. If Part 3 repeats Part 2, you have wasted a hundred marked words.

The development impact criterion asks a single question: if you are funded, will something that matters change in your country, and could anyone check? The four parts answer it in sequence.

What the panel penalises

The CSC's feedback names the traps. Some applicants write about how a scholarship would make them personally successful rather than how their work contributes to development. Some assume that a developmental-sounding subject is enough. Neither earns marks. Everything in this statement should point outward from you to the people and institutions that will change.

Part three: Part 1, beat by beat (200 words)

The zoom, around 90 words

Open on the problem, sized with an exact number, then move down a level at a time.

Variant one, the zoom.

"Cardiovascular and respiratory disease causes most deaths from non-communicable illness in my country, and an estimated one in three cases is undiagnosed until late stage. In Kesra Province the burden is heaviest in the dense settlements around the port, where air pollution, tobacco smoke and no preventive care combine."

Variant two, the contradiction.

"Our national programme screens for hypertension at every primary clinic, yet 61 per cent of the people it finds are never followed up, because the clinic has no clinician who can read the result and act on it."

Variant three, lived experience converted.

"I grew up in Dunmore District, where the brick kilns employ children from the age of eight. I now run the research that measures how many, and the answer is far higher than any official figure."

Variant four, the scarcity claim.

"There are fewer than sixty clinical officers in the country with training in cardiopulmonary care, and none of them works outside the capital."

Anchor every figure. The panel cannot check a figure with no source. Name it in a clause, not a footnote: "according to the national census", "in the ministry's 2024 survey".

Why it persists, around 40 words

One or two sentences on why the problem has not been fixed. This is where you earn the national and institutional anchor the CSC lists in its criteria. Name the rule, plan or institution that fails to reach the people you care about. "The 2023 Battery Waste Management Rules recognise licensed recyclers only, so the workers who handle most of the waste cannot register."

Theme and sector, around 70 words

Name the theme in a full sentence, using the form's exact wording, and say how your study connects to the wider sector's gap. Then say in one clause why this study, and why you.

"That is why I have chosen the theme Strengthening resilience and response to crises, and why I will study engineering and policy together, to design recycling that is safe, profitable and open to the people already doing it."

Do not restate the whole problem. The theme sentence should add the connection to the sector and to your study. It should not repeat the numbers.

Part four: Part 2, beat by beat (100 words)

The shortest part has the most work to do. It answers a single question the panel can act on: where do you go and what do you do first?

The three beats.

1. The institution and role (about 40 words). Name the body you will join, or the district you will start in, and your role there. "I will join the Provincial Child Protection Commission as a policy analyst."
2. The skills, from named modules (about 35 words). Say which skills you will bring and where you learn them. "Using the policy-simulation methods taught by Professor Calder..." This is the link between your study and your impact, and it is a listed indicator.
3. The first target (about 25 words). A number and a date that falls inside the first year. "4,000 workers registered and 800 tonnes moved into licensed channels."

Strong versus weak.

Weak: "On my return I will use my knowledge to improve healthcare and work with the government and stakeholders to make a difference."

Strong: "Within a year I will join the Provincial Health Directorate as an analyst and use the biostatistics from my course to evaluate our screening programme, starting with the 40 clinics in Kesra."

Name the institutional door. "A think-tank" is a category. "The Centre for Energy and Environment Policy" is a door.

Part six: Part 4, beat by beat (100 words)

This is the part applicants skip, and it is a listed indicator: the extent of benefit and how impact could be measured. Panels trust applicants who say how they could be proved wrong.

The two-level structure.

1. Primary indicators (about 40 words). Whether the intervention works. Workers registered, tonnes collected, share of children working, recovery rate.
2. Secondary indicators (about 30 words). Whether lives change. Income, injuries, school completion, dropout.
3. Data source and checker (about 30 words). Where the numbers come from and who verifies them. A dashboard, a school census, household surveys, a statistics office, an audit.

Name the instrument.

"Annual School Census completion and dropout ratios will be compared with similar villages outside the pilot, and the Provincial Statistics Office will verify the results."

Include a feedback loop. "I will publish results each year so partners can check my claims" or "regular reviews will let me adapt the intervention". It shows accountability, which is in the heading of this part.

Do not invent an indicator. Use what your work genuinely produces. A real qualitative outcome beats an invented number.

Part seven: two full sample sets

Sample set one, battery circularity (theme: Strengthening resilience and response to crises)

Bracketed labels show structure. Do not include them. All names are invented.

Sample one, Part 1

Electric mobility is creating a waste problem that adopting countries are least equipped to manage. Emerging economies are projected to retire 9.4 million tonnes of lithium-ion batteries by 2030. My country alone will retire 212,000 tonnes of electric three-wheeler batteries a year by 2032, yet licensed plants can process only 11 per cent of that.

The rest moves through informal workshops. In Ashbury Yard, Port Marrow, 38,000 workers break open batteries by hand, and acid run-off has contaminated the canal that irrigates the city's market gardens. Every gram of battery-grade lithium and cobalt is imported, so each battery dismantled informally also sends recoverable metal and foreign exchange abroad. The 2023 Battery Waste Management Rules recognise licensed recyclers only, so the workers who handle most of the waste have no route into the system.

This is a resilience problem. A break in imported mineral supply, or a spill in a dense settlement, would hit workers, farmers and manufacturers together. That is why I have chosen the theme Strengthening resilience and response to crises, and why I will study engineering and policy together at Westmoor University, to design recycling that is safe, profitable and open to the people already doing it.

Sample one, Part 2

Within a year of returning I will join the Centre for Energy and Environment Policy (CEEP), a Port Marrow think-tank, as a circular-economy analyst. Using the policy-simulation methods taught by Professor Ines Calder, I will model how the Battery Waste Management Rules would change if informal workshops could register as collection partners, and present the results to the Ministry of Environment. In parallel I will run the first pilot in Ashbury Yard: 4,000 workers registered and 800 tonnes of battery waste moved into licensed channels, tracked through a battery passport, a digital record that follows each battery.

Sample one, Part 3

Over ten years I aim for three outcomes: 75,000 informal workers in certified operations, 9,000 tonnes of battery waste a year collected formally, and 92 per cent recovery of lithium, cobalt and nickel through closed-loop recycling, in line with the National Circular Economy Roadmap 2040. Today no informal worker can register, and licensed plants have capacity for 11 per cent of retired batteries.

Phase one, 2028 to 2030, is a pilot in three recycling clusters beginning with Ashbury Yard, run through CEEP: 2,400 tonnes collected and 8,000 workers trained and registered. Phase two, 2031 to 2034, scales to 12 cities with recyclers and vehicle makers as partners, reaching 9,000 tonnes a year and 40,000 workers. Phase three, 2035 to 2038, completes the network and adopts the improved recovery methods tested in phase two, reaching 75,000 workers and 92 per cent recovery.

Primary beneficiaries are the 75,000 informal workers, who move from unsafe, unrecorded work to protective equipment, training and social-security access. Secondary beneficiaries are small manufacturers, who gain a domestic source of recovered metal, and households that return used batteries for a refund. Tertiary beneficiaries are residents of recycling neighbourhoods, whose air and water improve, and the Ministry of Environment, which gains data it does not currently hold.

Because the model rests on registration and tracking rather than one city's geography, it can be replicated in other manufacturing waste streams.

Sample one, Part 4

Evidence will sit at two levels. Primary indicators test whether the intervention works: informal workers registered each year, tonnes collected as a percentage of batteries retired, and the percentage of lithium, cobalt and nickel recovered. CEEP will draw these from battery passports and cluster-level audits. Secondary indicators test whether lives change: the share of recycled batteries returned to use, battery-related fires and injuries recorded at clinics, and changes in registered workers' income and social-security enrolment. Annual household surveys and incident reports will supply these, and I will publish results each year so partners and the Ministry can check my claims.

Sample set two, child labour (theme: Access, inclusion and opportunity)

Sample two, Part 1

Child labour affects roughly one child in ten worldwide. My country's last census recorded 8.4 million child workers, and reform has stalled because inspectors visit most worksites less than once a year. In Tarn Province 3.1 per cent of children aged five to fourteen work. In Dunmore District, where I grew up, the figure is 6.7 per cent, and the brick kilns that dominate its economy employ an estimated 24,000 children.

Dunmore shows why national policy has not worked. Power over land, kilns and local officials sits with a few families, so those with the most to lose from enforcement control whether it happens. Policy is written for the average child, while the children at risk are concentrated in perhaps 200 hamlets that no one has mapped. Kiln owners are also the local lenders, so many families repay debts with their children's labour.

Under the theme Access, inclusion and opportunity, I will study public policy at Halden University to learn public finance, evidence-based reform and econometric methods, so that Dunmore's savings groups, schools and officials can be brought into one system that keeps children in class and out of the kilns.

Sample two, Part 2

On return I will join the Provincial Child Protection Commission as a policy analyst and use the econometric methods from my course to test, in my home district, a model that links the annual dividends of women's savings groups to their children's school attendance. I will design it with the Dunmore Women's Savings Federation, whose 310 groups already hold the community's trust, and pair it with a reporting system in which villagers are rewarded for flagging children out of school. Methods, partners and a first cluster of villages will be agreed within six months.

Sample two, Part 3

Within ten years I aim to bring Dunmore's child labour rate from 6.7 per cent to below 1 per cent, to enrol and retain 24,000 children currently at work, and to have the model adopted by the Commission as provincial guidance. I also want villagers to report cases themselves, so that enforcement no longer depends on inspectors who rarely visit.

Year one is research: a survey of 60 villages and GIS mapping of kiln hamlets to find the 200 or so highest-risk hamlets. Year two is a pilot in 12 of them, linking dividends to school attendance and launching community reporting. Years three to five extend the model across Dunmore with the Commission, with measurable falls in child labour and rises in attendance expected by year five. Years six to ten extend it to the rest of Tarn Province. Each phase ends with a public review alongside the Commission, so that results are checked before the model grows.

Primary beneficiaries are the children working in kilns, who gain a school place and a childhood. Secondary beneficiaries are the women in the 310 savings groups, around 6,200 members, whose groups gain larger and more predictable dividends. Tertiary beneficiaries are district officials and the Commission, who gain a verified, mapped picture of where children are at risk, which they do not currently have.

Because the model uses institutions that already exist, savings groups and village schools, it can be repeated in other districts at low cost.

Sample two, Part 4

Impact will be measured at two levels. Primary indicators: the share of working children in the mapped hotspots, the number of women organised into savings groups, and the annual growth of their dividends, tracked on a GIS dashboard shared with the Commission. Secondary indicators: school completion, dropout and enrolment ratios from the Annual School Census, compared with similar villages outside the pilot. Pre- and post-intervention surveys in every phase will evidence change independently, and the Provincial Statistics Office will verify the results. I will also use my study year to refine these methods and protect children's data.

What both sets do. They zoom from a global figure to a named local place. They explain why the problem persists by naming a rule or an incentive. They name the theme once, in a full sentence. They name an institution and a role in Part 2, and a first target. They give baselines, targets and dates in Part 3, tier their beneficiaries, and keep their phases consistent with their outcomes. They separate indicators into two levels and name who verifies the data.

Part nine: common mistakes, and the fix

Part ten: checklists

While drafting

• A global, national and local figure, each sourced
• One sentence on why the problem persists, naming a rule or institution
• The theme named once, in the form's wording
• Part 2 names the institution, the role and the first target
• Skills in Part 2 tied to named modules or academics
• Three outcomes, each with a baseline, a target and a date
• Three dated phases that sum to the outcomes
• Three tiers of beneficiary, with the primary tier counted
• Two levels of indicator, with data sources and a checker
• One line on scale or replication

Before submitting

• No repetition between the four parts
• Every figure sourced and every name spelled correctly
• No claim about personal success in place of development impact
• Every acronym defined on first use
• The full word count used in each part
• The route home in Part 2 matches the career plans and the study plan
• A national anchor named: a rule, plan or capacity shortage
• Nothing here contradicts my employment entries or personal statement
• I could defend every number if asked