Household Budget and Consumption Basket Study

Added Jul 2026 3 design docs

Economics students meet Engel's law as a sentence in a textbook: as household income rises, the share of spending that goes on food falls. It is one of the oldest empirical regularities in the discipline, and it can be tested in a single neighbourhood in a single month with nothing more than a notebook and ten willing families. Yet most households in India have never seen their own spending written down by category, which is why a family earning a decent monthly income can still be surprised at the end of every month, and why the phrase household budget usually means a vague intention rather than a document.

The intern runs a seven-day expenditure diary study across ten consenting households of deliberately different income levels. A short intake questionnaire in google-forms captures household size, earners and monthly income band, each family logs every rupee spent for a week on a printed diary sheet, and roughly 700 line items are categorised and analysed in excel to produce expenditure shares, food shares, an Engel scatter and per-capita comparisons. The findings become a 16-18 page report written in google-docs with a one-page profile for each household, a reusable budget planner workbook other families can actually download and use, and an explainer poster designed in canva.

Completing the project takes the intern through household survey design, consent and privacy handling for financially sensitive data, expenditure classification into consistent categories, share and per-capita normalisation, and the interpretation of a real empirical law against a small and messy sample. This is the exact skill set behind consumer research, market sizing and development economics fieldwork, and the public repository leaves the intern with an original micro-dataset and a genuinely useful tool to point recruiters at.

Related projects

College Canteen Demand and Pricing Study

Every college canteen runs on guesswork. The contractor raises the samosa from 15 to 20 rupees, sales dip for a fortnight, and nobody can say whether the loss in volume was worth the gain in margin, because no one has ever drawn a demand curve for a samosa. Students grumble that the cold coffee is overpriced while the thali sells out by half past one, and the two facts are treated as unrelated complaints rather than as evidence about how price-sensitive each item really is. It is the closest thing a first-year economics student has to a laboratory. The intern turns that laboratory into a study. A short price-ladder questionnaire built in google-forms asks at least 120 students across two campus canteens how many units of five named items they would buy in a week at four different prices, producing demand schedules that are then converted in excel into arc elasticities, revenue curves and a revenue-maximising price for each item. A three-day footfall and queue count adds observed behaviour beside the stated answers, and the results become a chart pack, a six-page pricing memo, a proposed menu card designed in canva and a ten-slide deck for the canteen management. Completing the project takes the intern from textbook demand theory to a defensible pricing recommendation: writing survey questions that do not lead the respondent, building schedules from raw responses, computing elasticity with the midpoint formula, spotting where stated intentions and observed queues disagree, and presenting a price change to someone whose income depends on it. Market research firms, pricing and revenue teams, FMCG management trainee programmes and consulting analysts all interview for exactly this reasoning, and the public repository shows the intern doing it on real data.

economicscanvaexcelgoogle-forms

PRD · HLD · LLD includedView

BusinessMedium

Policy Brief on a Government Welfare Scheme

India runs some of the largest welfare programmes in the world, from the mid-day meal that feeds crores of schoolchildren to the rural employment guarantee that sets a floor under village wages, and every Union Budget moves thousands of crores between them. Most public argument about these schemes runs on headlines and hearsay, because almost nobody outside the policy world opens the budget documents, the audit reports or the Standing Committee minutes where the actual record sits. Yet the currency of that world is small: a six-page policy brief that a busy official or an MP's researcher can finish in ten minutes and act on. The intern learns to write one. You choose a single centrally sponsored scheme, reconstruct five years of budget estimates, revised estimates and actual spending in excel, work out coverage, utilisation and per-beneficiary cost, and build an evidence log in notion that pins every claim to a document and page. The findings become a 2,000-word brief drafted in google-docs following the standard issue, evidence, options and recommendation format, a scored options matrix, a one-page leave-behind designed in canva, and a 12-slide walk-through deck. Completing the project takes the intern through skills the development and policy sector tests for directly: reading government financial statements without flinching, separating nominal from real spending, synthesising audit and evaluation evidence without exaggeration, appraising options against explicit criteria, and writing to a hard word limit for a reader who has ten minutes. Think tanks, legislative fellowships, policy consulting firms, CSR teams and competitive examinations all reward exactly this, and the public repository gives the intern a brief that stands as a work sample.

economicscanvaexcelgoogle-docs+1

PRD · HLD · LLD includedView

BusinessEasy

Public Transport Fare and Usage Analysis

A student living eleven kilometres from campus faces a decision every single morning that no economics class ever formalises for her: the bus costs ₹15 but takes fifty minutes and may not come, the metro costs ₹40 and takes twenty-eight, the shared auto costs ₹25 and leaves when it fills, and the app cab costs ₹180 and is unthinkable on a normal day. Multiply that choice by a few million commuters and it becomes the central question of urban transport economics, where fares, waiting time, reliability and household income interact to decide who moves freely through a city and who does not. The intern turns one city corridor set into a fare and usage study. Published fare charts for bus, metro and shared auto are compiled into a fare-per-kilometre matrix for three chosen corridors, stopwatch observations at stops measure real headways and crowding, and a commuter questionnaire in google-forms gathers 80 responses on mode choice, monthly commuting spend and willingness to switch. Everything is modelled in excel into fare-per-kilometre comparisons, a generalised cost that prices waiting time, and an affordability ratio against stated income bands. The findings become a 12-14 slide decision deck built in powerpoint for a fictional city mobility cell, three one-page corridor factsheets designed in canva, and a fare affordability calculator any commuter can use. Completing the project takes the intern through transport economics in miniature: unit-cost normalisation, valuing time as money, observational field measurement, survey-based stated preference, and the translation of analysis into four costed recommendations aimed at a real decision maker. Infrastructure consultancies, urban policy institutes and mobility startups interview for exactly this ability to move from a stopwatch and a fare chart to a defensible recommendation.

economicscanvaexcelgoogle-forms+1

PRD · HLD · LLD includedView