Center of Data of Economic Decision-making (CoDED)

A unified system to fix the broken data foundation for Vision 2047

India’s ambition to become a $30 trillion economy by 2047 demands a planning system rooted in timely, granular, and credible data. Yet most states today operate with delayed GSDP estimates, unreliable administrative datasets, and district-level numbers that are mechanically apportioned rather than measured. The very institutions responsible for producing this data (the Directorates of Economics & Statistics (DES)) are often under-capacitated, structurally weak, and unable to generate accurate, disaggregated information. Districts, despite being the true engines of growth, lack both the data and the analytical systems required for meaningful planning.

In a country where each state resembles a small nation and each district functions as a distinct economy, such data gaps make effective policymaking nearly impossible. Recognising this deep structural challenge; and responding to the Hon’ble Prime Minister’s call to make the district the “fulcrum of development”, Pahle India Foundation established the Center of Data for Economic Decision-Making (CoDED).

The Center rebuilds India’s broken data foundation through three integrated pillars.

1. Strengthening Statistical Systems in DES
Most states depend on the Directorate of Economics & Statistics (DES) to produce their economic data, but DES often lacks the staff, tools, and systems needed to generate accurate and timely information. Administrative data arrives late or in poor shape, methods are outdated, and district figures are usually rough estimates rather than real measurements. This leaves states planning with weak or incomplete evidence. The CoDED fixes this by strengthening DES from the inside out: cleaning and organising data, modernising processes, training officers in updated methods, and helping put in place simple, reliable systems that consistently produce high-quality state and district numbers. In short, CoDED turns DES into a dependable source of economic intelligence that governments can actually use for planning and decision-making.

2. District-led Development
The second pillar empowers districts to generate and act upon their own economic data.

2.1. Bottom-up DDP Estimation:
The current GDP apportionment process flows top-down: national à state à district, based on national ratios that rarely capture on-ground realities. CoDED inverts this method by proposing a bottom-up estimation of District Domestic Product (DDP) through three primary surveys:

Annual Survey of Industries (ASI) to capture organized manufacturing,
Labour Force Survey (LFS) to estimate secondary sector value added, and
Annual Survey of Unincorporated Enterprises (ASUSE) for tertiary sector insights.

This approach not only creates a more accurate baseline but also enables real-time tracking of key performance indicators (e.g., labor force participation rate).

2.2. District Blueprints and Economic Planning:
District blueprints are developed using PIF’s TSP3 framework, which moves from Target Setting to SWOC Analysis, then to Pathway Design, and finally the identification of three key growth drivers. Targets are set for each district’s GDDP and sectoral growth. A stakeholder-led SWOC analysis maps local strengths, weaknesses, opportunities, and constraints. The Pathway Design stage creates a sequenced roadmap of necessary reforms, priority projects, and resource allocation. The process concludes by selecting three high-impact growth drivers per district, based on inputs from District Collectors and stakeholder inputs along with DDP data, to focus efforts and achieve measurable development outcomes.

3. Policy Intelligence from Official, High-Frequency and Alternate Data

Using Existing Government Data for Inclusive Growth and Revenue Mobilisation

India already produces rich economic data through official surveys and administrative systems, yet much of this data remains under-used for active policymaking, while official GDP and GSDP estimates arrive with long time lags that limit their usefulness for real-time planning. CoDED addresses these twin challenges by utilizing official datasets, high-frequency and alternate indicators into timely, actionable policy intelligence.

Using microdata from the Household Consumption Expenditure Survey (HCES), CoDED focuses on the bottom 10 percent of households to assess whether growth is reaching the poorest, and inform welfare targeting and. Through the Annual Survey of Unincorporated Enterprises (ASUSE), CoDED analyses the unincorporated enterprise sector and links enterprise activity with GST registrations and filing behaviour to help state governments identify economically active but non-compliant or under-reporting firms. This enables targeted compliance strategies, GST base expansion, and higher tax revenues without increasing statutory rates.

Even with stronger systems and bottom-up DDP, states still lack timely economic intelligence because official GDP and GSDP arrive with long delays. CoDED addresses this by integrating fast-moving, high-frequency data, such as electricity use, GST collections, night-time lights, mobility trends, digital payments, and feeder-level power data, into planning. These indicators track real activity far more quickly than traditional statistics. Using them, CoDED builds subnational and sectoral nowcasting systems that estimate current economic conditions before official releases and reveal district-level trends in real time. PIF’s nowcasts have already shown high accuracy nationally and in Maharashtra. With monthly estimates, continuously updated models, and automated dashboards, states gain real-time visibility and can respond to shocks and opportunities as they unfold.

Together, these interventions transform how India plans, monitors, and delivers growth: bottom-up, state- and district-first, and future-ready.

PIF has signed formal MoUs with three states— Assam (June 28, 2023), Madhya Pradesh (May 21, 2025), and Maharashtra (July 31, 2025)—to pioneer bottom-up GDDP estimation and strengthen state statistical systems.

Nine-step roadmap to build district-level GDP estimates

What Happens When Bottom-Up GDDP Counts India’s Invisible Economy
A bottom-up pilot survey conducted in four districts of Uttar Pradesh revealed massive underestimation from the unincorporated sector in the manufacturing sector’s Gross Value Added (GVA), with Meerut’s official figure of ₹1.94 lakh lakhs nearly tripling to ₹4.82 lakh lakhs (+147%), Varanasi showing a +120% increase, and Kanpur +79%, leading to a total underestimation of nearly ₹9 lakh lakhs (~99%) across just these four districts. Such reliance on top-down estimates distorts ground realities, weakening planning, budgeting, and resource allocation. To achieve India’s Vision 2047, it is imperative to build systems that generate reliable, bottom-up data we can trust.

Comparison of GVA Estimates from Pilot Survey and Current DDP Series in Manufacturing Sector (derived from the allocation method)

The Pahlé India Foundation (PIF) team brings together top leadership and technical expertise to drive bottom-up data reforms. Guided by Dr. Rajiv Kumar, PIF’s Chairperson, former Vice Chair of NITI Aayog, and supported by leaders like Shaurya Doval and Ravi Pokharna, the initiative is anchored by Shri Ashish Kumar, former DG of the Central Statistical Office, MoSPI, and Dr. Payal Seth, an economist and Fellow. We also have dedicated teams working across Delhi, Assam, Madhya Pradesh, and Maharashtra, ensuring robust research, policy analysis, and on-ground implementation.

CoDED will deepen work with states to modernise DES, complete district blueprints backed by better data, and fully embed high-frequency, nowcasting-based dashboards into routine decision-making. The goal is to turn this into a scalable, national template for district-led, data-driven governance on the path to Vision 2047.