Faculty of Arts and Social Sciences School of Economics ECOS3002 Development Economics Mid-sem exam review Faculty of Arts and Social Sciences School of Economics ECOS3002 Development Economics Mid-sem exam review Exam logistics and overview Exam logistics • The university exams office is responsible for administering the exam, through the special ‘In-semester Test for: ECOS3002’ Canvas site. • All official information on the exam and its administration, comes from them, and overrides anything I say in this video or elsewhere on the ECOS3002 Canvas site. • I will not be available on the day of the exam, the Ed site will be offline the day of the exam, and exams cannot be submitted by email. • Any exam-related issues will have to be dealt with through official University systems (e.g., Special Consideration), and approval of appeals is not guaranteed. • This video is providing an informal review of the logistics of the exam, and a review of some of the relevant content on the exam. • I highly recommend logging in to the exam site as soon as you have access, reading through everything, and making sure you have access to all the materials, resources, and software necessary for an online exam. Exam details Date of test: 11/10/2021 (Monday) Start: 14:00 AEST Duration: 1 hours and 30 minutes (90 minutes). This includes: • 10 minutes reading time, but you are free to start the test as soon as you are ready. • 30 minutes of upload time to allow you to upload your files as per your test instructions. Do NOT treat this as extra writing time. The upload time must be used solely to save and upload your files correctly as per the test instructions. Manage your time carefully. Check that you have saved and named your file correctly and uploaded the correct file. If your time runs out while you are uploading this is not considered a technical issue. • Materials required: (i) scientific calculator, and (ii) a sheet of blank paper with a writing instrument (pen or pencil), OR a digital drawing tool. • Your final exam submissions will be in the form of a pdf (only). Analysis • The exam will not involve complex calculations or manipulations in Excel, however it will involve basic operations that you can implement on a scientific calculator. • You will also need to create a figure – you can do that using pen/pencil and paper, or a digital drawing tool. Either way you will need to upload your figure as a pdf. Exam format Question type Points Recommended time spent Question 1 Draw, calculate, interpret 15 15 minutes Question 2 Short answer: interpret a quasi-experiment 10 10 minutes Question 3 & 4 Short answer 5 each 5 minutes each Question 5 Short essay 15 15 minutes Academic honesty • It should go without saying that the exam is to be taken completely individually. Use of any method to communicate with classmates during the exam is forbidden. • Beyond that, it is an open book exam. The exam is designed so that you won’t get a huge benefit from searching online or in your textbook, so don’t get tempted to plan to just look things up for your exam responses. But you are certainly welcome to use either to look up concepts, definitions, etc. Faculty of Arts and Social Sciences School of Economics ECOS3002 Development Economics Mid-sem exam review Content overview Content of exam • Everything up to and including week 7 is fair game: lectures, tutorials, and textbook chapters. • In practice we the exam is most heavily focused through week 6, with light coverage of week 7 (enough to review the lecture video). Week Week Beginning Lecture Lecture Topic(s) / textbook chapter(s) 1 9 Aug Lecture 1 Chapter 1: What is development? Indicators and issuesChapter 4 (part 1): Impact evaluation 2 16 Aug Lecture 2 Chapter 4 (part 2): Impact evaluationChapter 3: History of thought in development economics 3 23 Aug Lecture 3 Chapter 5: Poverty and vulnerability analysisChapter 6: Inequality and inequity 4 30 Aug Lecture 4 Chapter 10: The economics of farm households 5 6 Sept Lecture 5 Chapter 18: Agriculture for development 6 13 Sept Lecture 6 Chapter 11: Population and development Chapter 12: Labour and migration • Chowdhury research vignette 7 20 Sept Lecture 7 Chapter 13: Financial services for the poor Chapter 1: What is development? Indicators and issues • The first question to answer about development is – what is it? How do we define it? How do we quantify it? • Our textbook posits 7 dimensions of development: 1. Income and income growth: totals like GDP, GNP, GNI, per capita, growth rate, PPP conversion. 2. Poverty and hunger: % below a poverty line (monetary), or a metric like calories. 3. Inequality and inequity: comparing top X% vs bottom Y%; inequity about opportunities. 4. Vulnerability: risk of poverty, vulnerability or susceptibility to adverse shocks (covariate and idiosyncratic risk), poverty traps? 5. Basic needs: human development: human capital (health, education), HDI, multidimensional poverty indices. 6. Environmental sustainability: intergenerational equity. 7. Quality of life: many broader theories, some outside economics. Within economics, Sen’s capabilities approach (focused on what you could do – freedom of choice), and Easterly’s 81 indicators of quality of life. Chapter 1: What is development? Indicators and issues • An approach to quantify well-being is through subjective measures, like “subjective well being” or happiness. • Provides a single-index measure, all encompassing, going beyond money. • But how well can we measure it? Easterlin paradox (1974), showing no correlation between income and happiness in OECD, seems to be overturned in developing countries (e.g., Deaton, 2008). • The dominant international development framework is the Sustainable Development Goals (declared in 2016 with targets for 2030) to replace the Millenium Development Goals (2000). Chapter 4: Introduction to impact evaluation and RCTs • An important trend in international development is to evaluate the effectiveness of international development programs and policies, using causal inference techniques. • The challenge for an impact evaluation researcher is that without a research design, data on programs and policies is almost always suffers from selection bias – because there are choices (on demand side or supply side of an intervention) about whether or not to take up an intervention, the take-up decision can be affected by hard-to-measure characteristics that also affect outcomes. • Then if outcomes differ between recipients and non-recipients of an intervention, was it because of those characteristics (which we can’t measure and control for), or the intervention? • Impact evaluation methods provide causal inference techniques to help us overcome selection bias. Chapter 4: Introduction to impact evaluation and RCTs • The randomized control trial (RCT) is considered the most rigorous or most scientific method to overcome selection bias. It is based on the clearest research design, with the weakest assumptions. • Because we explicitly randomize participants into treatment and control groups, we control the allocation of treatment, so treatment allocation shouldn’t be correlated with hard-to-measure characteristics. • Even here, whether “randomization worked” on unobservables is untestable, however we do balance checks on observables to verify. • With an up-front research design, RCTs lead to clear, simple analysis. Two common methods to estimate effects from RCTs are ITT (an average treatment effect) and ToT (a local average treatment effect). Chapter 4: Introduction to impact evaluation and RCTs • Because of randomization, RCTs are highly internally valid. But they may suffer from external validity issues, especially if we work with an opportunistic sample (e.g., a single NGO or company). This can also cause a pioneer effect. • Because RCTs are heavily controlled/planned, they can be subject to common experimental biases – e.g., Hawthorne effect (being studied changes behavior), John Henry effect (control group tries to catch up). • RCTs rely on the SUTVA assumption. Sometimes we may need to randomize a larger scale (e.g., village / neighborhood) to mitigate spillovers. • In some cases we can leverage “natural” randomization (e.g., that a government implemented). There we want to particularly check that randomization worked. Chapter 4: Introduction to impact evaluation and RCTs • There are other credible ways to do an impact evaluation. • In economics these are known as “quasi-experimental” methods because they try to imitate what a pure experiment does – separating treatment from the characteristics of the treated units. • Common methods in applied economics include: • Regression discontinuity design (RDD) • Differences-in-differences (DiD) • Instrumental variables (IV) • Propensity score matching (PSM) Chapter 4: Introduction to impact evaluation and RCTs • While we can learn a lot from these methods, they all suffer drawbacks relative to RCTs: ◦ RDD only estimates a local average treatment effect (LATE), though we model the treatment allocation process. ◦ DiD relies on assumptions about unobservable counterfactual trends. ◦ IV relies on an untestable assumption, the exclusion restriction, and again only gives us a LATE, typically for an undefined population. ◦ PSM relies on strong assumptions around how observables allow us to balance unobservables. • What are the threats to validity of these quasi-experimental designs, and how would you test for them? Chapter 3: History of thought in development economics (post-WWII) • 1950s-1960s: “glory years” of recovery, big push theories used to drive recovery in Europe. • 1970-1982: growth boom in 50s-60s didn’t lead to poverty reduction. Development agenda expanded beyond pure growth, to look at pro-poor growth and other dimensions of development. Lots of fiscal spending and debt accumulation. 1970s were also a major inflationary period. • 1982-1997. Era starts with debt crises, as high inflation means high and unsustainable interest rates. To combat this, we get structural adjustment reforms under so-called Washington consensus, which was about opening up markets and reducing the role of the state in markets (deregulation, privatization, lowering of trade barriers, etc). Chapter 3: History of thought in development economics (post-WWII) • However Washington consensus was too abrupt a change, many countries couldn’t adapt. 1990s considered a “lost decade” for development, particularly in Africa. • 1997-2019. As a corrective, renewed role of the state in complementing the market, multidimensionality in development, more customized development policies. Emergence of MDG agenda (2000) with eye to 2015. • End of cold war (1989) brings greater interest in aid performance, and emergence of the impact evaluation revolution in development economics, in parallel to the credibility revolution in economics. Key leaders such as Abhijit Banerjee, Esther Duflo, Michael Kremer (Nobel Prize, 2019). Chapter 5: Poverty and vulnerability analysis • Poverty means not having a sufficient amount and/or quality of something. Measurement then involves defining that amount/quality, and then identifying which individuals/households don’t have a sufficient amount/quality. • Typically we want a monetary measure. While we might like to use income, in practice we typically use consumption (expenditure), adjusted for, e.g., CPI (inflation over time), PPP, access to public goods, converted to per capita level. • Set a poverty line – e.g., extreme poverty line (enough money for required daily caloric intake), normal poverty line (often 2x extreme poverty line), international poverty line (PPP$1.90 per day for extreme poverty, and PPP$3.10 per day for normal poverty). Chapter 5: Poverty and vulnerability analysis • A poverty profile graphs a ranking of households by expenditure (x-axis), then the level of expenditure on the y- axis. Poverty line is a horizontal line. Poverty gap is the gap between poverty line and y, for households below poverty line. • FGT developed a theory of poverty measures, build on Sen’s work. 1. Headcount ratio (proportion of poor in population): If = 0, 0 = / 2. Poverty gap index (average of poverty gap as a fraction of poverty line): if = 1, 1 = ∑=1 − 3. Severity of poverty index (average of square of poverty gap as a fraction of poverty line): If = 2, then 2 = 1� =1 − 2 Chapter 5: Poverty and vulnerability analysis • Other poverty measures consider multidimensionality within a period in time, or poverty over time (never poor, transitory poor, chronic poor, persistent poor). • Vulnerability summarizes poverty over time into the probability of being poor. Inverse of resilience. • Question about whether poverty traps exist. Usually build on a self-reinforcing dynamic whereby lacking enough of an asset (wealth, knowledge, health, psychological well-being, etc) makes it hard to climb out of the trap. Chapter 6: Inequality and inequity • Our tools for inequality analysis are built on the Lorenz curve, which plots cumulative % of population ranked by expenditure level (x-axis) against, the cumulative % of total expenditure (y-axis). • Poverty profile is like probability distribution function, Lorenz curve like cumulative distribution function. • 45-degree line shows perfect equality. • Gini coefficient: fraction of area between Lorenz curve and 45-degree line, compared to area under 45-degree line. • Runs between 0 (complete equality) to 1 (maximum inequality). • Income shares: income held by richest x% of population and poorest y% of population. Kuznets ratios then take ratios of these, removing units. Can have x=y, but don’t have to. Chapter 10: The economics of farm households • Farm households in developing countries: 25% of world population, 75% of world poverty. • First need to define a farm household – based on joint production, consumption and or reproduction. • The farm household model is one of the core models in development economics. • It captures labor allocation and leisure tradeoffs, alongside the role of land and capital • It provides a core model to analyze how market failures and frictions (in labor, goods, land, credit, etc), which impede the access of households to markets, can lead to behaviors and outcomes that might seem puzzling or irrational on first glance. Separability captures whether a household behaves as if its consumption and production decisions are independent, which is only possible if it is fully integrated in markets. If it is integrated, then it can set MC=MB on all margins. Chapter 10: The economics of farm households • Net buyer / net seller distinction, for interpreting welfare effects of prices. • A key question is whether family farms can compete – should we reinforce them (through policies), or encourage the movement out of agriculture? May really be about how fast. • Smallholder farmers are often highly exposed to uninsured risk. To deal with this, they can use: • Risk management: acting in advance to reduce probability and magnitude of risks. I.e., if expected impact is p*M, then try to reduce p and/or M. • Risk coping: dealing with risks after they happen. Chapter 10: The economics of farm households • The standard household model assumes unitary decision-making. • But in some contexts/decisions this may be too simplistic. Non-unitary decision-making models allow for multiple power brokers in the household. • Most common application husband and wife. • This provides another possibility for separability to be violated. In this case, the question is whether the power balance (e.g., between husband and wife) is affected by their production decisions or not. If it is, then separability may be violated (consumption and production choices intertwined). Chapter 18: Agriculture for development • Agriculture has played a key role in human development through history, and still can today, but in modern times is often given less attention. 1. As a source of growth 2. Source of livelihoods and well-being 3. As a locus for resource saving and environmental services • Agricultural pricing is a key dilemma for developing world governments: higher prices benefit farmers but cost emerging urban consumers. Do you try to manipulate prices (in either direction)? How do you manage imports and exports? • When thinking about agricultural policy, need to remember this is a market particularly structured around long value chains. Chapter 18: Agriculture for development • One of the greatest miracles for humanity in the last century was the so-called Green Revolution, which allowed mankind to greatly improve efficiency in producing basic calories, mostly through staples like maize, rice, wheat. • Humanity has made great progress in eliminating famines. • Going forward, however, most food demand growth will be in developing countries. Bennett’s law says demand for variety and quality of food grows with incomes. Yet arable land is becoming more scarce and there are other environmental pressures like on water supply. Need a Green Revolution 2.0 to meet this new challenge: more investment in agricultural research, better trade agreements, progress on climate change and adaptation, better ways to deal with food emergencies. • Need to enhance basic food security, alongside providing for balanced diet that people want. Chapter 18: Agriculture for development • Ultimately such a revolution goes to the farmer level: will they adopt new technologies and means of production? Issue of technology adoption and how tech adoption choices interact with market failures (credit, labor, food, risk, land, etc) and other mechanisms like social learning and psychological biases. • The farm household model gives us a framework to think about reasons why they might not adopt (and why that might not be irrational). Chapter 11: Population and development • The study of population, or demography, is of keen interest for economists. How the evolution of population affects, and is affected by, economic factors. • Birth and death rates natural rate of increase in population • Infant mortality and life expectancy at birth • Total fertility rate (TFR) • Replacement fertility rate: 2.1 • Population pyramids provide an insightful way to summarize population data • A key question is the economics of fertility – when, how, and why people choose to have children. Thomas Malthus thought that population will always tend to outrace food supply, but he has been proven wrong – birth rate tends to go down as people become richer. Why? Chapter 11: Population and development Economic insights on fertility: 1. Fertility outcomes are subject to willful choice. 2. Fertility decisions are determined by calculus of advantage (utility maximization) over economic gains and costs. 3. Methods of fertility control are available. Breaking out 2., some benefits and costs: 1. Child is a source of income, so can compare PV benefits > PV costs. 2. A child is a source of insurance, particularly in old age. 3. A child is a source of satisfaction. As people get richer, they prefer “higher quality” children. Gary Becker (1981) provided explanation for this. All these forces point to higher birth rates in developing countries. Chapter 12: Labor and migration • Analysis of labor is different in developing countries, because few people can afford to be openly unemployed, due to lack of government support programs. • Government capacity to regulate employment also weak. • In practice, in many developing countries, many workers, oftentimes the majority, in the informal sector (agriculture, wage work, microenterprise). • The poor are almost exclusively in this sector. • Of course the formal and informal sectors interact, and economists have looked at how prices and competition can leads to spillovers between these sectors. • A key current issue is how to increase labor force contribution of women. Chapter 12: Labor and migration • A big part of long-run economic development through structural transformation is the urbanization of countries. • Workers move from rural to urban areas, and % of urban crosses 50% threshold. • Basic model of migration in economics is the Beckerian-style Harris-Todaro framework, where migration is basically about expected cost versus benefit from migrating. • “New migration economics” is a richer analysis that extends the basic Harris-Todaro framework to allow for local market failures, the fact migration could be part of a household livelihood strategy, and a focus on remittances (leading to contracting dilemma between migrant and sending family). Chapter 12: Labor and migration • International migration is an important phenomenon for many countries, including for developing countries in sending migrants (and receiving remittances, more important than foreign aid for many developing countries), and “brain circulation.” • Why might a migrant remit? 1. Repayment (migration costs, broader human capital investments) 2. Securing future inheritance 3. Social security (e.g., supporting parents) 4. Insurance (responding to shocks) 5. Altruism How would we test between these explanations? Chapter 12: Labor and migration • Migration can benefit sending communities by: 1. Enhancing returns to education 2. Increasing income and consumption in sending communities 3. Enhancing investment 4. Brain circulation 5. Provide labor market opportunities for others Faculty of Arts and Social Sciences School of Economics ECOS3002 Development Economics Mid-sem exam review Exam preparation Exam prep • See the module under Canvas/Modules/Mid-sem exam prep. Provides: • Exam overview and logistics (similar content as this video). • Study tips • Sample exam questions. Sample from a previous exam I gave in ECOS3002. Not a direct model for this exam, but an indication of the style of questions I give on exams. • Consult hours: • Regular hours in week 8: Alex -- Wednesday 4:30-5:30, Geneve -- Thursday 8-9 am, Russell – Thursday 4- 5 pm • Additional consult hours in week 8: Alex 3-4 pm on Thursday-Friday (7-8 October), Geneve 4:30-6:30 pm on Friday 8 October. • I highly recommend posting any exam-related queries on Ed (or PMs to instructor or tutors) before 3 pm on Friday 8 October. Ed will be unavailable the day of the exam. Study tips • Make your own summary of the material. • The textbook website also provides chapter overviews. • Read through tutorial, end-of-chapter, and questions from the textbook website, and see if you can work through how to answer them in your head. • Can you remember the concept behind the calculations in Excel? • Can you interpret all the results, including the figures? • Try to explain key concepts to yourself, a friend, classmate, etc. We internalize and master things by applying them, not by passively consuming them. Can you think of new applications or questions around the concepts? Good answers • Good exam answers are accurate, concise, and to the point. • May be valuable to very quickly outline your answer (e.g., on a note pad), before typing it. Ask yourself: what are the important points to make here? • Long answers with lots of extraneous information will not generally be as well rewarded as precise answers – sometimes show your understanding as much by what you don’t write, as what you write. It shows a level of judgment, in terms of what you include, emphasize, and argue. • No need to rewrite the question in the answer, or to copy-paste definitions or other content.
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