A 120-credit, three-year program engineered for moderate to high-end placement outcomes — anchored in quantitative rigor, computational fluency, and structured Civil Services preparation.
To be a globally-recognized centre of excellence in economics and public policy education that develops analytically rigorous, ethically grounded, and socially conscious graduates capable of shaping the economic future of India and contributing meaningfully to global economic discourse.
Deliver a curriculum that is quantitatively rigorous, technologically current, and grounded in Indian economic realities, benchmarked to globally-leading economics programs.
Cultivate analytical, computational, and communication skills that prepare graduates for high-value careers in finance, consulting, technology, public policy, and civil services.
Foster a culture of evidence-based policy thinking through capstone research, field experiments, and partnerships with policy institutions (NITI Aayog, RBI, J-PAL South Asia).
Build a vibrant intellectual community through industry engagement, alumni networks, and a strong placement pipeline targeting moderate-to-high pay packages.
Integrate civil services preparation into the academic mainstream, recognizing that public service is a credible and valued career outcome.
Graduates demonstrate strong quantitative and analytical capabilities in their professional roles, applying microeconomic theory, macroeconomic frameworks, econometric methods, and computational tools to solve real-world economic and policy problems.
Graduates excel in high-value career paths across investment banking, management consulting, data science, public policy, development economics, or civil services, achieving moderate to high-end compensation outcomes and rapid career progression.
Graduates contribute to evidence-based policy formulation and implementation, whether as government economists, think-tank researchers, development practitioners, or civil servants, with demonstrated social impact.
Graduates pursue advanced education (MA, MSc, MBA, MPP, PhD) at globally-reputed institutions or professional certifications (CFA, FRM, FRM, MicroMasters), adapting to evolving economic landscapes and technological change.
Graduates exhibit professional ethics, civic responsibility, and inclusive thinking; they engage with society's economic challenges through volunteer work, public discourse, or institutional leadership.
Apply microeconomic, macroeconomic, and behavioural theory to analyze consumer/firm behaviour, market structures, aggregate economic phenomena, and policy interventions.
Use mathematical economics, statistics, and econometric methods (linear regression, panel data, time series, causal inference) to model and test economic relationships using real-world data.
Implement economic and data-analytical solutions using Python, R, SQL, and modern ML/AI tools; build reproducible analyses and deploy models.
Analyze public policies using cost-benefit analysis, program evaluation, and political-economy frameworks; communicate policy recommendations through structured briefs.
Demonstrate deep understanding of Indian economic structure, history, and current policy debates, situated within global economic contexts.
Communicate complex economic and policy ideas clearly through writing (academic, professional, policy briefs), public speaking, and visual presentation in English.
Demonstrate readiness for UPSC and state PSC competitive examinations through structured GS coverage, answer-writing skills, current-affairs awareness, and personality development.
Apply ethical frameworks to economic decisions; recognize the social, environmental, and intergenerational consequences of economic choices.
Design and execute original research projects; replicate published work; pre-register hypotheses; communicate findings to academic and policy audiences.
Demonstrate workplace readiness: resume building, networking, interview skills (technical, case-based, behavioral), professional etiquette, and salary negotiation.
Collaborate effectively in cross-functional teams; lead group projects; manage time and deadlines; resolve conflicts constructively.
Recognize entrepreneurial opportunities at the intersection of economics, policy, and technology; pursue startup, fellowship, or innovation pathways.
Color encodes driver geography: ◼ Global · ◼ National · ◼ Regional · ◼ Combined
India's ₹5 trillion → ₹10 trillion economy ambition needs economists understanding fiscal policy, banking reform, factor markets (land, labour, capital), and federalism. Domestic policy roles at NITI Aayog, RBI, MoF, EAC-PM, state-level economic advisory roles, multilateral think-tanks.
Indian financial services growing at 11-13% CAGR; quant/IB hiring at major banks (Goldman, JPM, Citi, MS) increasingly accepts BA Econ. CFA/FRM-aligned syllabus prepares for global standards.
World Bank, IMF, ADB, J-PAL South Asia, IDinsight, ideas42, 3ie hiring on causal-inference + Indian field experience. RCT/quasi-experimental design is the global gold standard.
Indian unicorns (Razorpay, Cred, Zerodha, Flipkart, Swiggy) hire economics+ML profiles at strong salaries. ML-for-economics is also a faculty area at top US/UK PhDs (Chicago, Stanford, LSE).
UPSC CSE remains India's most-competitive examination. Telangana/AP state PSCs also active. The BA structure embeds 9 GS-depth IAS courses + 9 LSRW communication modules covering ~70% of Mains content.
Platform economy (Uber, Amazon, Flipkart, Zomato, Razorpay) creating economist roles for pricing, marketplace design, regulation. Crypto/Web3 emerging at slower pace but with global salaries.
India's Net-Zero 2070 commitment + global ESG mandates create roles in climate finance, carbon markets, ESG ratings, sustainable supply chain. Indian climate think tanks (CEEW, ICRIER, TERI) hiring.
KL's Vijayawada base lets students engage with AP/Telangana economic ecosystem: irrigation economics, agri-marketing, MSME clusters, KLEF startup ecosystem, Pharma/biotech belt. Local government internship pathways at AP Economic Development Board, Telangana State Economic Advisor.
Each bar shows the range from entry-band ◯ to peak-band ●. Salary data from peer-program outcomes.
FIN-FIN-ECONQUANT-MATH-1/2QUANT-STATS-2QUANT-ECONO-1/2ECON-MICRO-1/2ECON-INDIAECON-GAME-THEORYPOLICY-ANALYSISall communicationECON-MICRO-1/2ECON-INDIAPOLICY-ANALYSISCOMP-TOOLSall communicationFIN-FIN-ECONECON-INDIAQUANT-STATS-2POLICY-PUB-FINCOMP-TOOLS-1/2COMP-MLCOMP-AIQUANT-STATS-1/2QUANT-ECONO-1/2QUANT-MATH-1/2/3QUANT-STATS-1/2QUANT-ECONO-1/2FIN-FIN-ECONCOMP-MLECON-INDIAECON-MACRO-1/2POLICY-PUB-FINPOLICY-ANALYSISIAS-POLITY-2All 9 IAS-* courses + 9 LSRW/COMM courses + ECON-INDIAPOLICY-PUB-FINPOLICY-ANALYSISECON-INDIAQUANT-ECONO-1/2ECON-DEVFIN-FIN-ECONECON-MACRO-1/2QUANT-STATS-2POLICY-PUB-FINBSc Economics (3 year) / BSc Economics & Economic History (3 year)
BA (Hons) Economics (3 year Tripos)
BA Economics (4 year)
Bachelor of Science in Economics (14-1) (4 year)
BSc Economics (Honours) (4 year)
BStat (Hons) (3 year) / BMath (Hons) (3 year) — econ via electives
BA (Hons) Economics under DU (3 year)
BA (Hons) Economics (4 year) — Liberal Arts
BS Economic Sciences (4 year)
BA (Hons) Economics (3 year)
◼ Navy = 14 credit trimesters (3 trims) · ◼ Gold = 13 credit trimesters (6 trims) · Total: 120
| # | Code | Course Name | Bucket | L/D | Cr | L | T | P | S | CH/wk | Trim | Prereqs |
|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | ECON-MICRO-1 |
Microeconomics I — Consumer & Producer Theory | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T01 | None |
| 2 | QUANT-MATH-1 |
Mathematical Economics I — Calculus & Linear Algebra | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T01 | (External: Class XII Math) |
| 3 | COMP-TOOLS-1 |
Computational Tools for Economists (Python & R) | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T01 | None |
| 4 | ENG-LINGUA |
Lingua Skill — English | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T01 | None |
| 5 | IAS-POLITY-INTRO |
Introduction to Indian Polity | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T01 | None |
| 6 | ECON-MICRO-2 |
Microeconomics II — Market Structures & Welfare | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T02 | ECON-MICRO-1, QUANT-MATH-1 |
| 7 | QUANT-MATH-2 |
Mathematical Economics II — Optimization & Dynamic Systems | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T02 | QUANT-MATH-1 |
| 8 | QUANT-STATS-1 |
Statistics I — Descriptive Statistics & Probability | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T02 | QUANT-MATH-1 |
| 9 | ENG-LANGUAGE |
Modern Indian Language | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T02 | ENG-LINGUA |
| 10 | IAS-POLITY-PROCESS |
Indian Political Process | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T02 | None |
| 11 | ECON-MACRO-1 |
Macroeconomics I — Aggregate Demand & Supply | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T03 | ECON-MICRO-1, QUANT-MATH-1 |
| 12 | COMP-TOOLS-2 |
Data Analysis with Python & R | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T03 | COMP-TOOLS-1, QUANT-STATS-1 |
| 13 | ECON-GAME-THEORY |
Game Theory & Strategic Decisions | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T03 | ECON-MICRO-1, QUANT-MATH-1 |
| 14 | IAS-HIST-ANCIENT |
Ancient Indian History | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T03 | ENG-LANGUAGE |
| 15 | IAS-GEO-INTRO |
Introduction to Geography | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T03 | IAS-POLITY-INTRO |
| 16 | ECON-MACRO-2 |
Macroeconomics II — Growth, Money & Open Economy | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T04 | ECON-MACRO-1, QUANT-MATH-2 |
| 17 | QUANT-STATS-2 |
Statistics II — Inferential Statistics & Distributions | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T04 | QUANT-STATS-1 |
| 18 | QUANT-ECONO-1 |
Econometrics I — Linear Regression & Cross-Sectional Methods | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T04 | QUANT-STATS-2, COMP-TOOLS-1 |
| 19 | IAS-HIST-MEDIEVAL |
Medieval Indian History | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T04 | ENG-LANGUAGE |
| 20 | IAS-GEO-PHYS |
Physical Geography | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T04 | None |
| 21 | QUANT-ECONO-2 |
Econometrics II — Panel Data, Time Series & Limited Dependent | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T05 | QUANT-ECONO-1 |
| 22 | COMP-ML |
Machine Learning for Economists | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T05 | QUANT-STATS-2, COMP-TOOLS-2, QUANT-ECONO-1 |
| 23 | ECON-INTL-TRADE |
International Trade & Finance | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T05 | ECON-MICRO-2, ECON-MACRO-1 |
| 24 | IAS-HIST-MODERN |
Modern Indian History | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T05 | IAS-HIST-ANCIENT |
| 25 | IAS-GEO-INDIA |
Geography of India | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T05 | IAS-GEO-PHYS |
| 26 | ECON-INDIA |
Indian Economy & Policy | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T06 | ECON-MACRO-2, POLICY-PUB-FIN |
| 27 | POLICY-PUB-FIN |
Public Finance & Fiscal Policy | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T06 | ECON-MICRO-2, ECON-MACRO-1 |
| 28 | DIGITAL-DIG-ECON |
Digital Economics & Platform Markets | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T06 | ECON-MICRO-2, ECON-GAME-THEORY |
| 29 | IAS-GOVERNANCE |
Indian Governance & Social Justice | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T06 | ENG-LANGUAGE |
| 30 | IAS-GEO-WORLD |
Economic & World Geography | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T06 | IAS-POLITY-PROCESS |
| 31 | FIN-FIN-ECON |
Financial Economics & Asset Pricing | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T07 | QUANT-STATS-2, QUANT-ECONO-1, ECON-MICRO-2 |
| 32 | ECON-DEV |
Development Economics | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T07 | ECON-MICRO-2, ECON-MACRO-2, QUANT-ECONO-1 |
| 33 | ECON-BEHAV |
Behavioural Economics | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T07 | ECON-MICRO-2, QUANT-STATS-1 |
| 34 | IAS-HIST-WORLD |
World History | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T07 | None |
| 35 | IAS-IR |
International Relations | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T07 | None |
| 36 | POLICY-ANALYSIS |
Policy Analysis & Program Evaluation | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T08 | POLICY-PUB-FIN, QUANT-ECONO-1 |
| 37 | COMP-AI |
AI Agents & LLMs for Economists | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T08 | COMP-ML, COMP-TOOLS-2 |
| 38 | SUSTAIN-ENV |
Environmental Economics & Sustainability | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T08 | ECON-MICRO-2, QUANT-STATS-2, POLICY-PUB-FIN |
| 39 | IAS-DISASTER |
Disaster Management | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T08 | IAS-HIST-ANCIENT, IAS-GOVERNANCE |
| 40 | IAS-SOCIETY |
Indian Society | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T08 | IAS-GEO-WORLD |
| 41 | PROJECT-CAPSTONE |
Capstone Project — Senior Thesis | ECON | DEPTH | 3 | 0 | 2 | 6 | 7 | 8 | T09 | QUANT-ECONO-1, COMP-TOOLS-2, COMP-ML, POLICY-PUB-FIN |
| 42 | DIGITAL-TOKEN |
Tokenomics & Web3 Economics | ECON | DEPTH | 2 | 2 | 1 | 3 | 3 | 6 | T09 | ECON-MICRO-2, ECON-GAME-THEORY, DIGITAL-DIG-ECON |
| 43 | QUANT-MATH-3 |
Advanced Optimization for Economists | ECON | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T09 | QUANT-MATH-2, ECON-MACRO-2 |
| 44 | IAS-SECURITY |
Internal Security | UPSC | LIGHT | 2 | 1 | 1 | 2 | 2 | 4 | T09 | IAS-HIST-WORLD, IAS-HIST-MODERN |
| 45 | IAS-ECOLOGY |
Ecology & Environment | UPSC | DEPTH | 3 | 3 | 1 | 2 | 4 | 6 | T09 | IAS-GEO-WORLD |
Teams of 3-4 conduct a structured survey of 30 households (urban + rural mix) to map consumption baskets, savings behavior, and informal credit use. Final deliverable: data set + 1500-word analysis + dashboard.
Virtual portfolio competition using TradingView simulator. Teams allocate ₹10 lakh hypothetical capital across 5 sectors and defend choices. Awards for best Sharpe ratio + best stock pick.
Visit local wholesale + retail markets; document price differences for 10 common commodities; analyze supply chain markup; present findings in 5-min presentation.
Teams build an interactive Streamlit/Dash dashboard pulling RBI/MoSPI/CMIE data for 10 key macro indicators (GDP, CPI, IIP, repo rate, fiscal deficit, etc.) with monthly updates and YoY comparisons.
Students role-play MPC members. Read latest MPR; debate rate decision; vote and publish "minutes". Compare with actual MPC decision.
2-hr challenge: design a 10-day Europe trip on ₹2 lakh INR budget across 4 currencies; navigate exchange rates, transaction fees, and PPP differences.
Teams design a small-scale behavioural experiment (default effects, anchoring, loss aversion) and run it on 30+ participants in campus/community. Pre-register on OSF; document findings.
Round-robin tournament of classic games (Prisoner's Dilemma, Ultimatum, Public Goods, Beauty Contest). Cash prizes; analyze patterns of cooperation/defection.
Day 1: theory of BATNA, ZOPA, anchoring. Day 2: live negotiation exercises with campus food vendors (with their consent) for bulk purchase discounts; report outcomes.
Teams pick a published paper from QJE/AER/JoP using publicly available data; replicate the main results in R/Stata; document deviations and extend with one new specification.
Open hackathon on India's Periodic Labour Force Survey (PLFS) data. Teams submit a 5-page insight brief on labour market patterns. Judges from NITI Aayog/IDinsight.
Live coverage of Union/State Budget. Sector-wise impact analysis; live tweet thread; evening panel discussion with faculty.
Teams use ML (random forests, gradient boosting) on a public policy dataset (poverty targeting, school dropout, MGNREGA outcomes). Deliverable: model + policy brief recommending implementation.
Enter an active Kaggle competition. Teams collaborate on baseline → improved model. Best team gets to attend a Kaggle Days event.
Visit Razorpay/Cred/Zerodha/Swiggy/Flipkart data team. Live data science problem-solving session with their analysts.
Teams identify a current Indian policy gap (PM-KISAN delivery, Mid-Day Meal coverage, electricity DBT pilot, BNPL regulation, etc.) and write a 4000-word NITI Aayog-style brief with theory of change, M&E framework, and budget estimate.
Students role-play MPs and bureaucrats; debate a fictional bill on say, "Gig Worker Social Security Act". Outcome: vote + committee report.
Day-long case study on a real Indian PPP (Delhi Metro, Mumbai Coastal Road, Dholera SIR). Analyze contract structure, risk allocation, outcomes.
Teams compete in a national-level case competition (HUL L'Oréal Brandstorm, McKinsey U-Connect, Bain BCC, Bain Bold, Boston Analytics). Faculty mentor each team.
Teams pick an Indian listed company; build 3-statement model + valuation; pitch in 10-min Buy/Sell/Hold recommendation. Judges from local PMS/broker firms.
Teams pitch a CSR project to a local Vijayawada firm using their declared CSR budget. Best pitches receive seed funding.
For students with summer internship offers — guided reflection on internship learnings, conversion strategy (PPO discussions), and creating a deliverable for the internship host.
Build an LLM-based tool for economics: paper summarizer, policy brief generator, market analyst chatbot. Demo on Day 2.
Senior bureaucrats + faculty conduct mock UPSC interview boards. Each student gets 25 minutes; detailed feedback provided.
Final-trimester intensive on capstone deployment: web/app/notebook artifact + public defense to industry panel + executive summary distribution to network.
Each student showcases their offer/admit/exam pathway through a poster + 5-min talk. Acts as institutional memory for next cohort.
Senior alumni return for full-day mentorship circles by sector (consulting/IB/tech/civil services/research). Each circle = 6-8 alumni + 15-20 students.
Every course maps 3–4 of these methods, with course-specific execution detailed in each course page. Each method below carries a concrete execution sequence and a four-level evaluation rubric. The fifteen methods span seven pedagogical clusters.
Instructor-facilitated questioning and adversarial debate that forces students to defend economic positions with theory and evidence.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Theoretical grounding | 30% | Arguments rest on correctly applied economic theory with explicit assumptions. | Mostly correct theory; assumptions implicit. | Theory referenced but loosely or partly misapplied. | Opinion with little theoretical basis. |
| Use of evidence | 25% | Cites relevant data/cases accurately and proportionately. | Uses evidence, minor gaps. | Sparse or weakly relevant evidence. | Assertion without evidence. |
| Engagement with counter-arguments | 25% | Anticipates and fairly rebuts the strongest opposing case; concedes honestly. | Addresses counter-arguments adequately. | Acknowledges but does not engage opposition. | Ignores opposing views. |
| Intellectual humility & revision | 20% | Post-debate note shows genuine, reasoned updating. | Some updating with reasons. | Minimal reflection. | No evidence of reconsideration. |
Students analyse a real decision-situation case, take a defensible position, and are cold-called to defend it under pressure.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Problem framing | 25% | Identifies the real decision and the binding constraints precisely. | Reasonable framing, minor omissions. | Describes the case but mis-locates the core decision. | Summarises without framing a decision. |
| Analytical use of course concepts | 30% | Applies course tools rigorously to the data in the case. | Applies concepts with small errors. | Mentions concepts without applying them to data. | No meaningful concept application. |
| Recommendation quality | 25% | Clear, actionable, risk-aware recommendation that follows from the analysis. | Clear recommendation, thin on risks. | Vague or weakly supported recommendation. | No clear recommendation. |
| Discussion contribution | 20% | Advances the class's thinking; listens and builds. | Solid, relevant contributions. | Occasional or surface contribution. | Passive / off-point. |
Students build, calibrate, and stress-test an economic model live in code rather than watching it derived on a board.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Model correctness | 30% | Model is economically and computationally correct; assumptions stated. | Minor errors not affecting conclusions. | Errors that distort results. | Model does not run or is conceptually wrong. |
| Calibration & data use | 20% | Parameters grounded in real data with sources. | Mostly grounded; some arbitrary values. | Weak grounding. | Arbitrary parameters. |
| Comparative-statics interpretation | 30% | Predicts then verifies; explains the economic intuition clearly. | Correct interpretation, thin intuition. | Describes output without intuition. | No interpretation. |
| Reproducibility & documentation | 20% | Clean, runnable, well-documented, version-controlled. | Runnable with light documentation. | Hard to follow / partial. | Not reproducible. |
Students reproduce the central result of a real economics/policy paper from its data, then probe its robustness.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Faithful reproduction | 30% | Reproduces the headline result exactly with clean code. | Reproduces with trivial differences. | Partial reproduction. | Fails to reproduce. |
| Methodological understanding | 25% | Explains the method and why each step matters. | Mostly correct understanding. | Mechanical, limited understanding. | Does not understand the method. |
| Robustness probing | 25% | Thoughtful specification change with correct interpretation. | Reasonable robustness check. | Superficial check. | None. |
| Research integrity & documentation | 20% | Transparent, honest about discrepancies, fully reproducible. | Mostly transparent. | Gaps in documentation. | Opaque / not reproducible. |
A timed, brief-driven sprint where students take raw data to a defensible analytical answer and a clean visual.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Data wrangling | 25% | Clean, correct, well-justified cleaning decisions. | Mostly correct cleaning. | Errors in cleaning. | Data not usable. |
| Analytical correctness | 30% | Method fits the question; conclusions valid. | Minor method issues. | Questionable method. | Wrong analysis. |
| Visual communication | 25% | One honest, clear, decision-ready chart. | Clear chart, minor flaws. | Cluttered or misleading. | Ineffective visual. |
| Finding & defence | 20% | Crisp finding, defends data choices under challenge. | Clear finding, partial defence. | Weak finding. | No defensible finding. |
Students produce a real-format policy brief for a named decision-maker, iterated through structured peer critique.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Problem & options clarity | 25% | Sharp problem statement; mutually exclusive, real options. | Clear, minor overlap in options. | Fuzzy problem or options. | Unclear. |
| Evidence & economic reasoning | 30% | Evidence and cost-benefit logic directly support the recommendation. | Sound reasoning, some gaps. | Weak or selective evidence. | Assertion-driven. |
| Feasibility & risk awareness | 20% | Realistic on political economy and implementation risk. | Notes main risks. | Limited feasibility thought. | Ignores feasibility. |
| Communication & format discipline | 25% | Crisp, BLUF, within length, decision-maker-ready. | Clear, slightly long. | Wordy / poor structure. | Not brief-format. |
Students play a structured economic game (market, auction, bargaining, macro-policy) and analyse the data their own behaviour generates.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Strategic reasoning in play | 25% | Decisions show clear strategic logic consistent with the setup. | Mostly strategic. | Inconsistent strategy. | Random play. |
| Theory–behaviour comparison | 35% | Rigorously compares observed data to equilibrium prediction. | Sound comparison, minor gaps. | Superficial comparison. | No real comparison. |
| Explanation of deviations | 25% | Explains deviations with correct theory. | Plausible explanation. | Weak explanation. | None. |
| Use of data | 15% | Uses the game's own data quantitatively. | Some quantitative use. | Mostly qualitative. | No data use. |
Students take assigned stakeholder roles in a contested economic decision and negotiate to an outcome.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Role fidelity & preparation | 25% | Deeply prepared; argues the role's real economic interests. | Well prepared. | Thin preparation. | Unprepared. |
| Negotiation skill | 25% | Creates value, uses BATNA, reaches sound agreement. | Competent negotiation. | Positional / limited. | Ineffective. |
| Economic reasoning | 30% | Positions grounded in correct political-economy logic. | Mostly sound. | Weak reasoning. | No economic basis. |
| Reflection on efficiency & equity | 20% | Insightful analysis of who gained/lost and why. | Reasonable analysis. | Superficial. | None. |
Students collect primary data from the real economy (markets, firms, households) and analyse it.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Research design & ethics | 25% | Sound instrument; consent and ethics handled well. | Reasonable design. | Design flaws. | Poor / unethical design. |
| Data collection quality | 25% | Real, careful, documented collection. | Adequate data. | Sloppy collection. | Unreliable data. |
| Analysis & interpretation | 30% | Correct analysis with honest interpretation. | Mostly sound. | Weak analysis. | Incorrect. |
| Limitations & humility | 20% | Clear-eyed about sampling and validity limits. | Notes main limits. | Few limits noted. | Overclaims. |
Teams own an ill-structured real problem across several weeks, defining sub-questions and producing a solution.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Problem decomposition | 20% | Decomposes ambiguity into sharp, tractable sub-questions. | Reasonable decomposition. | Vague decomposition. | None. |
| Integration of concepts | 30% | Weaves multiple course concepts coherently. | Uses several concepts. | Thin integration. | Disconnected. |
| Solution quality | 30% | Feasible, evidence-based, creative solution. | Solid solution. | Weak solution. | Unworkable. |
| Teamwork & process | 20% | Strong collaboration, accountability, peer-validated. | Good teamwork. | Uneven contribution. | Dysfunctional. |
Students absorb content before class; class time is spent entirely on application, problem-solving, and doubt-clearing.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Pre-class preparation | 25% | Consistently prepared; strong readiness scores. | Usually prepared. | Inconsistent. | Unprepared. |
| In-class problem-solving | 35% | Solves and explains challenging problems. | Solves standard problems. | Needs heavy support. | Disengaged. |
| Peer explanation | 20% | Explains clearly to peers; strengthens others. | Helpful to peers. | Rarely contributes. | None. |
| Metacognition (exit tickets) | 20% | Precisely identifies own gaps. | Identifies gaps. | Vague. | None. |
Conceptual questions answered individually, then debated in pairs, then re-answered — peer teaching corrects misconceptions.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Conceptual accuracy | 40% | Strong concept accuracy across the term. | Generally accurate. | Frequent misconceptions. | Persistent errors. |
| Quality of peer argument | 35% | Persuades with correct reasoning; open to being corrected. | Reasonable arguments. | Weak arguments. | Non-participative. |
| Reasoning justification | 25% | Justifies answers with sound logic. | Adequate justification. | Thin. | None. |
Students translate technical economics into a public-facing op-ed, explainer thread, or short video for a lay audience.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Economic accuracy | 30% | Simplifies without distorting the economics. | Mostly accurate. | Some distortion. | Inaccurate. |
| Accessibility & craft | 30% | Compelling, clear to a lay reader. | Clear, less engaging. | Jargon-heavy. | Inaccessible. |
| Structure & narrative | 20% | Strong hook, single clear idea, clean arc. | Decent structure. | Loose structure. | Disorganised. |
| Response to critique | 20% | Revises substantively from peer feedback. | Some revision. | Minimal. | Ignored feedback. |
Students formally review each other's analytical work against a rubric, building evaluative judgement.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Quality of feedback given | 35% | Specific, fair, actionable, rubric-anchored feedback. | Useful feedback. | Vague feedback. | Unhelpful. |
| Critical judgement | 30% | Accurately identifies real strengths and flaws. | Mostly accurate. | Misses key issues. | Poor judgement. |
| Responsiveness to received critique | 35% | Substantive, well-justified revisions. | Reasonable revisions. | Minimal. | None. |
An extended, original project that integrates the whole course, mentored in studio mode and defended publicly.
| Criterion | Wt | Excellent | Proficient | Developing | Beginning |
|---|---|---|---|---|---|
| Integration of course concepts | 30% | Uses the full course toolkit coherently and correctly. | Uses most concepts well. | Partial integration. | Fragmented. |
| Originality & rigour | 25% | Original question, rigorous execution. | Sound, less original. | Derivative or loose. | Weak. |
| Execution & reproducibility | 25% | Polished, complete, fully reproducible artifact. | Complete, minor gaps. | Incomplete. | Unfinished. |
| Defence & communication | 20% | Compelling defence; handles Q&A expertly. | Solid defence. | Shaky under questioning. | Cannot defend. |
Each trimester is validated against the structural rules: 5 courses · 3 Econ + 2 UPSC · 4 Depth + 1 Light · 13-14 credits · 28 CH/wk classroom.
| Trimester | Courses (5) |
Econ (3) |
UPSC (2) |
Depth (4) |
Light (1) |
Credits (13-14) |
CH/wk (28) |
|---|---|---|---|---|---|---|---|
| T01 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 14 ✓ | 28 ✓ |
| T02 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 28 ✓ |
| T03 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 28 ✓ |
| T04 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 14 ✓ | 28 ✓ |
| T05 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 28 ✓ |
| T06 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 28 ✓ |
| T07 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 14 ✓ | 28 ✓ |
| T08 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 28 ✓ |
| T09 | 5 ✓ | 3 ✓ | 2 ✓ | 4 ✓ | 1 ✓ | 13 ✓ | 30 ✓ |
Contact hours are a clean 28 CH/wk classroom for most trimesters (T09 carries 30 CH/wk due to the lab-intensive Capstone). Total program: 120 credits across 9 trimesters.