How space can provide useful hints and what is the forecast for the 2020 Presidential election
Monitoring the COVID-19 Crisis From Space (Sloan Review, 8 min read) Studies show light emissions can successfully quantify local economic activity, local levels of income, and electricity usage. These methods in real-time can track changes in economic activity, monitor conflicts and natural disasters. Impact of COVID on China was noticeable from Jan onwards with these methods even before official lockdown.
Treasury Market Liquidity During the COVID-19 Crisis (Liberty Street Economics, 8 min read) A column compares how market liquidity of Treasury securities in March 2020 with the past fifteen years, (including 2007-09 financial crisis). Current Bid-Ask Spreads were at their widest, order book depth was comparable to 2007-2009 period, price volatility was also higher and so was trading volume.
What the Index of Leading Indicators Tells Us About the 2020 Presidential Election (Angry bear, 2 min read) A column applies econometric to predict 2020 election. In all of the recent head-to-head match-ups with Joe Biden, Trump trails. Current Index of leading Indicators stands at -6.7% – this favours Biden.
Economist criticism of epidemiologist and why pandemic trilemma doesn’t exist in reality
A New Indicator of Bank Funding Cost (BIS, 24-page read) Rollover risk is usually measured by the spot IBOR-OIS spread, to estimate expected funding stress- forward IBOR-OIS spreads (FFS) can be constructed. FFS are better predictors of economic and banking activity than alternative spreads on rollover risk and credit risk.
Navigating the Pandemic Trilemma (Project Syndicate, 6 min read) Pandemic has revealed a trilemma: it is impossible to have a medically healthy society, a healthy economy, and a healthy democracy at the same time. In the real world (unlike theory), these trade-offs are not absolute; rather negotiable. For example, widespread testing and contact tracing entails a partial loss of privacy but would be acceptable to save lives.
What Does this Economist Think of Epidemiologists? (Marginal Revolution,4 min read) Epidemiologists fail to account for: long-run elasticities of adjustment ( in the long run you learn which methods of social distance protect you the most), public choice considerations (policy moves from impatient politicians), Lucas critique (agents within a model, knowing the model, will change their behavior) and selection bias (early models were calibrated from Italy data hence more pessimistic).
Why money multipliers are now useless and how random sampling can tackle COVID-19.
Multiplier misconceptions (Econlib, 4 min read) Money multiplier models taught in the textbook are not as useful as they change over time. Before 2008 the interest rate was controlled by adjusting the number of reserves. Today, it also includes adjusting the interest rate paid on reserves.
Data Needs for Shutdown Policy (VoxEU, 5 min) To decide when to ease lockdown would require calculation on how widespread the virus is. Current testing for the virus is focused on those showing severe symptoms or at high risk due to resource constraints. One potential solution – random testing of the population to identify the true infection rate.
Repo market and leverage ratio in the euro area ( Banca D’ ITALIA, 17-page read) New evidence on the effect of the leverage ratio (LR) on repo market activity in the euro area. Banks are found to exert market power towards non-bank financial institutions by applying lower rates and larger bid-ask spreads.LR is not a significant factor in the widening of bid-ask spreads. This evidence lessens the concern of additional LR reporting and disclosure requirements
How to increase IMF resources and stress in the non-bank sector
The IMF Will Need More Resources to Fight the COVID-19 Pandemic (Peterson Institute for International Economics, 5 min read) As only half of the IMF’s $1.2trn is available for lending the fund must mobilise resources through either; asking members to increase bilateral lending, expanding central bank swap lines with some IMF role in triggering their use, using repos to put country holdings of foreign government debt to use or the IMF issuing $500bn in SDR.
A Cost-effective Way to Help Emerging Markets Fight COVID-19 (FT, 3 min read) An IMF-funded scheme to guarantee fx-denominated debt service in EM (ex China) is needed to counteract looming BoP crises given unprecedented capital outflows from EM, collapsing commodity prices and the economic disruption triggered by quarantines.
Non-banks Failing Coronavirus Stress Test (OMFIF, 3 min read) Regulators must reassess the risks from leverage in the non-bank financial sector and its interconnectedness with the wider economy to determine why the Fed has had to resort to its GFC crisis toolkit despite a more robust banking system.
Why current funding stress differs from 2008 and COVID’s impact on cash use
The COVID-19 Cash Out (Project Syndicate, 4 min read) The high likelihood of banknotes transmitting the coronavirus will push faster adoption of card payments, particularly in Asia which already has well developed cashless infrastructure. Cultural and technological factors have kept cash dependency higher in the West but COVID-19 could well change this.
USD Funding Stresses Rise But This Is Not Like 2008 (Variant Perception, 1 min read) A less leveraged, more highly capitalised and tighter regulated banking system leaves the financial system more robust than in 2008. Moreover, today’s funding pressures are concentrated in offshore USD markets.
A black swan with a permanent impact and an analysis of travel bans and virus transmission
The Impact of COVID-19 on the Housing Market: A Wake Up Call to Markets (Dr Housing Bubble, 3 min read) Ongoing uncertainty due to the virus will significantly impact the housing market. Real estate is a lagging indicator to stocks and as job losses mount a correction will start to become clear.
Is the COVID-19 Outbreak a Black Swan or the New Normal? (MIT Sloan Management Review, 9 min read) Putting people before profits, introducing resilience and risk reduction as integral parts of a business model and embracing reduced travel as a component in the fight against climate change are ways that the current black swan event will have a permanent impact on business.
Tracking Coronavirus in Countries With and Without Travel Bans (ThinkGlobalHealth, 3 min read) Despite 88 countries imposing travel bans with China COVID-19 continued to spread. Nevertheless, it did delay the spread of the virus, particularly in countries which took measures to reduce community transmission.
Ending dollar dominance and deciphering term premia during hiking cycles
The Rise and Fall of International Currencies (Project Syndicate, 8 min read) Two new books, Currency Stagecraft and How Global Currencies Work, offer insights into the history, politics and economics of global currencies. Both see ending dollar dominance as a much-needed and inevitable outcome.
Do Treasury Term Premia Rise Around Monetary Tightenings? (Liberty Street Economics, 5 min read) There is no evidence that term premia increase sharply when the Fed shifts to a tightening cycle with rising LT rates instead attributable to upwardly revised expectations for ST rates. But a consideration going forward is that expectations over the Fed’s balance sheet policy will impact term premia.
Modelling market-implied RWA and yield curve inversion under an accommodative policy stance
Variability in Risk-weighted Assets: What Does the Market Think? (BIS, 55 page read) A new measure of market-implied RWA shows significant differences in RWA between banks / countries prior to 2016 due to; shares of less transparent assets, capital constraints and country-specific factors. Basel III reforms have reduced the RWA variability.
Predicting Recessions Using the Yield Curve: The Role of the Stance of Monetary Policy (Boston Fed, 18 page read) Yield curve inversion during a period of “unusually accommodative” monetary policy such as Q3 2019 overstates the likelihood of recession.
No Sight of Next Recession: Business Cycle Index Update (iMarket Signals, 2 min read) This BCI using readily available economic and market data would have predicted the last seven recessions with a 20-week leading signal. The current signal is comfortably in expansionary territory.
Linking large datasets and how to predict high yield returns
The Promise of Automated Historical Data Linkage (VoxEU, 6 min read) Using automated techniques to link historical data is no worse than using “hand links” providing a practical solution to linking multiple large datasets.
A Simple Introduction to Neural Networks (Less Wrong, 24 min read) A introductory guide to machine learning focusing on neutral networks. Designed as a stand-alone although the earlier nine chapters are also available.
Are High-Yield Returns Predictable? Key Metric Suggests Yes (Advisor Perspectives, 1 min read) High yield corporate bonds exhibit predictable returns over time with the starting yield the key driver, even during the financial crisis.
The Fed and CBDCs
The Digitalization of Payments and Currency – Some Issues for Consideration (BIS, 14 page read) Lael Brainard points to concerns over data privacy and lack of financial protections for consumers as big tech rather than banks dominate payment systems. For any sovereign digital currency the Fed must consider the impact on the payment system, how resilient it would be, the intermediaries needed and the cross-border implications.
Financing constraints for intangible assets and liquidity risks from large CCPs
Central Clearing and Systemic Liquidity Risk (Federal Reserve, 39 page read) Large central counterparties create procyclical liquidity risks despite their role in improving financial stability. Macroprudential stress tests focused on liquidity are needed to determine the impact of shocks to central counterparties on system wide liquidity.
Productivity and Finance: the Intangible Assets Channel (OECD, 61 page read) Firms with higher intangible assets face tighter financing constraints due to difficulties in measuring and valuing such assets, with a detrimental impact on productivity growth.
On Socially Influenced Preferences (Stumbling And Mumbling, 3 min read) The case for a progressive consumption tax rests on the basis that other people’s spending makes us spend more. Behavioural and informational externalities also influence spending.
Exchange rates moves reconnect with risk and what we have in common with algos
Exchange Rate Reconnect (VoxEU, 4 min read) Since the financial crisis movements in the US dollar can be explained by changes in global risk metrics and (net) foreign bond purchases, pointing to a structural break in the earlier disconnect between exchanges rates and risks.
Financial Trading Bots have Fascinating Similarities to People (The Conversation, 4 min read) Anticipating others and concealing their true identity are two common characteristics between humans and algorithms. Understanding how algorithms interact could develop the next stage of AI, think self driving cars.
New indicators on recession forecasting and news-based sentiment
Recession Forecasting With the Federal Reserve Bank of Chicago’s Newly Released Brave-Butters-Kelley Indexes (iMarketSignals, 4 min read) The new BBKIs are constructed using 500 monthly macroeconomic timeseries indicators and aims to measure monthly real GDP growth and a number of its components. Despite a two-month time lag, they seem to be accurate and currently show no signs of a recession. [Bullish equities]
News-based Sentiment Indicators (IMF, 56 page read) Sentiment either spikes or trends up before financial crises according to a new “text based” uncertainty measure developed by IMF researchers. The dataset is for 20 countries and can be used an Early Warning Indicator (EWI)
Can too much information hurt?
Too Much Transparency Makes the World More Opaque (Marginal Revolution, 1 min read) Transparency is highly desirable, but at certain times it can prove a double-edged sword. The NY Times latest plan of having all presidential candidate interviews on the record will fail to achieve its intended objectives. We will likely no longer see off-the-record uncomfortable comments.
Forecasting Energy Commodity Prices: A Large Global Dataset Sparse Approach (Dallas Fed, 24 page read) The authors show improved forecasting accuracy for energy prices several quarters ahead, particularly gas, using a quarterly global VAR dataset for the 33 largest economies. More accurate predictions could have important macro consequences for the world’s energy dependent countries.
New insights into fx reserve composition using more granular central bank data. Does a “don’t know” response on Japanese inflation expectations actually contain useful information.
The Currency Composition of Foreign Exchange Reserves (BIS, 38 page read) The BIS uses new data across 60 economies and finds that the choice of currency in FX reserves is affected by the correlation between the local currency and G3 FX and also the invoice currency in trade.
“Don’t know” Tells: Calculating Non-Response Bias in Firms’ Inflation Expectations Using Machine Learning Techniques (Bank of Japan, 24 page read) The Bank of Japan tried to determine whether firms that say they “don’t know” in the Tankan survey’s questions on inflation expectations, actually do “know” something. They use some clever machine learning techniques and find that some do “know”, but it doesn’t impact the overall results of the Tankan survey.
The Cost of Clearing Fragmentation (BIS, 47 page read) The inability to net trades across exchanges and clearing houses can distort market prices. This study finds that US dollar swap contracts do trade with price differences across US and UK exchanges. This suggests there is a collateral cost issue.
Banks Do Not Create Money Out of Thin Air (VoxEU, 5 mins) It’s a widely held view that banks create money at will, but this article asserts that money creation stems from the assets of both parties in a transaction. For example, when using a credit card, the assets stem from the individual using the bank card, which are the individual’s future payments. The private bank in return must hold healthy assets and the local currency reserves issued by the central bank in order to be trusted. If there are doubts about either of these things, it will lead to a run on the banks. [Bullish banking sector]
Market structure is changing. Some like the advent of machine learning could enhance investor returns, while others like fragmented clearing are adding an additional cost.
What Machine Learning Will Mean for Asset Managers (Harvard Business Review, 7 min read) Harvard asserts that machine learning (ML) will actually reverse the trend towards passive investment. ML can make more accurate forecasts by using alternative data (eg images and sound), employ non-linear modelling, reduce human biases and be quickly implemented without regulatory approvals (unlike say the auto industry) . [Bullish ML quant managers, bearish traditional passive}
The Cost of Clearing Fragmentation (BIS, 30 min read) Latest BIS research shows that an architecture based on multiple but fragmented central counterparties (CCPs) lead to daily opportunity costs of $80 million for end users. This happens mainly because global liquidity dealers cannot net trades cleared in different CCPs. [Bearish banks]
Crunching the numbers, oil may not impact the dollar as much as people think. There’s growing scepticism around ESG and what’s the best US indicator to look at?
Oil Prices, Exchange Rates and Interest Rates (Dallas Fed, 32 Pages) This study attempts to disentangle oil prices, US interest rates, and the value of the dollar in an attempt to clarify the simultaneous relationships interlinking them. Essentially finds less than 10% of the variability of the dollar is due to oil prices.
Regression to Trend: Another Look at Long-Term Market Performance (Advisor Perspectives, 4 min read) A regression trendline of the S&P Composite Index indicates that current equity prices are 125% above their long-term trend. The last time this happened was in 2000 when the index overshot by 137%. Mean reversion implies that the current strong equity figures can’t sustain for too much longer. [Bearish US Equity]
When Can We Stop Talking about ESG? (CFA Blogs, 3 min read) ESG analysis may be a redundant part of standard investment valuation because many of the ideas driving it are already incorporated in the long-term strategies of successful non ESG businesses. Further, many corporate executives resist ESG discussions and find them to be overly focused on moral concerns, which is causing ESG proponents to rethink their messaging. [Bearish ESG]
The Most Important & Overlooked Economic Number (Advisor Perspectives, 5 min Read) The Chicago Fed National Activity Index is a forward-looking metric that forecasts economic conditions in the coming months, with specific focus to production, employment, personal consumption, and inventory levels. The index currently forecasts weaker employment numbers and increasing layoffs in the next few months. [Bearish US]
Asset managers will have to implement AI-based cost reducing solutions to cope with structural shifts. Punitive regulation for credit market making activity has direct impact on liquidly and prices, and dealer inventory data now a major source of advantage.
Adapting to a New Normal in European Asset Management (McKinsey & Company) European Asset Managers were less affected by the switch to passive strategies and successfully dealt with the last decade’s macro structural changes. But McKinsey argues the next decade will be more difficult. Profit margins are likely to fall not least because of lower bond yields. Therefore cost control will be key.
Commonality in Credit Spread Changes: Dealer Inventory and Intermediary Distress (NBER Working Paper) A broad financial distress measure and a dealer corporate bond inventory measure can statistically explain about 50% of the excess variation of credit spread changes beyond structural credit risk factors.
In the topsy-turvy world of negative rates, there are likely to be many unintended consequences. One is that IT systems may not actually be able to process negative rates. Bank regulation may also have negative effects too. For example, new research has found that stress tests have led to lower lending than would otherwise be the case.
Negative Interest Rates Threaten to Choke Bank IT Systems (itnews) Negative interest rates can strangle banks’ IT systems. Australia’s and New Zealand’s top banks confess they are struggling to make their transactional and mortgage systems cope with a switch to negative interest rates. [Bearish bonds]
Correlations, Value Factor Returns, and Growth Options (SSRN) Finds that looking at implied correlations could improve the profitability of value-based trading strategies. [Bullish value factor]
The Effect of U.S. Stress Tests on Monetary Policy Spillovers to Emerging Markets (Fed Working Papers) Fed finds that banks reduced their credit supply because of the stress tests. Also, finds that lending to emerging markets would have been higher had the US not introduced stress tests for their banks. [Bearish EM]
US national accounting suggests companies are using offshore investments to hide income from taxes. Shadow banks could be harming liquidity. But in the new world, we could see the rise of digital currencies.
A Big Borrower and a Giant Corporate Tax Dodge? How Best to Describe the U.S. External Balance Sheet (Council on Foreign Relations) Brad Setser argues that the US is analogous to a household that can borrow indefinitely at a very low rate, as the US’s financial assets can barely cover the US debt liabilities. The equity side is seen as a corporate tax dodge for US-based multinationals.
The High Stakes of the Coming Digital Currency War (Project Syndicate) Harvard Professor Kenneth Rogoff suggests that Facebook’s proposal of Libra has intensified the competition of digital currencies between countries. He also warns how state-sanctioned digital currencies may disrupt the scene. [Bearish bitcoin]
The Side Effects of Shadow Banking on Liquidity Provision (Liberty St Economics/ NY Fed) Since the mid-1990s, shadow banks have started eating into traditional banks’ share in the term loan business. The increasing presence of shadow banks also has an indirect, negative impact on the liquidity insurance that credit lines provide to corporations.
Not all stock market losses have been created equal – there is a clear hierarchy and we feature Ben Carlson from Ritholtz exploring it. Also, a great piece on what the next trends in asset management are and why nearly 90% of U.S. stock market funds failed to beat their indexed benchmark over the past 15 years.
Trends That Matter in Asset Management (A Wealth of Common Sense) It’s not all about fundamentals – professionals overtaking amateurs, a surge in target-date funds and quants replacing star managers now matter too.
Don’t Take Their Word For It: The Misclassification of Bond Mutual Funds (NBER) This working paper examines empirical evidence to explain how mutual fund managers could misclassify their holdings, and how such misreporting behaviours are more incentivised after continuous periods of large negative returns.
The Hierarchy of Stock Market Losses (A Wealth of Common Sense) Ben Carlson explains how people may lose money in the stock market differently – this depends on if they’re in developed markets, emerging markets, or just individual stocks.
A number of uncertain macro factors are weighing down on equity valuations while at the same time value stocks are making a comeback, riding the volatility and possible undervaluations.
Tracking Macro Factors In Portfolio Strategies(The Capital Spectator) Runs a number of regressions to estimate the impact of different macro factors on diversified ETF portfolios. Finds that influence of such factors varies by market and over time.
The Revival In The US Equity Value Factor Rolls On(The Capital Spectator) Explores the recent revival in value stocks. It’s likely caused by heightened concern over slowing economic growth refocusing the market’s attention on undervalued assets. [Bullish value factor]
Using Payment System Data to Forecast Economic Activity(Aprigliano, Ardizzi, Monteforte) Models large amounts of retail payments data in Italy to show that tracking such transactions more closely helps make better GDP predictions.
It might be hard to trade Trump’s erratic decisions –but a bunch of investors have made a fortune from his tweets. The question is whether they have used insider information. Plus, there could be an unbeatable model to predict fund performance and no one has taken much notice.
The Best Predictor of Stock-Fund Performance (Morningstar) Turns out buying stocks held by successful funds is a reliable trading strategy for success.
“There Is Definite Hanky-Panky Going On”: The Fantastically Profitable Mystery of the Trump Chaos Trades (Vanity Fair) Investigates a number of large e-mini trades on the S&P500, often made right before the market closes and strangely right before a big geopolitical market shaker. Argues that this could be a case of insider trading and calls for heavier regulatory watch.Gulp.
The Banking View of Bond Risk Premia (Haddad, Sraer) Shows that the net exposure of the banking sector to interest rate risk, as measured through banks’ average income gap, strongly forecasts future bond excess returns.
We feature a paper looking at utilising machine learning in predicting crisis and why oil modelling remains robust.
Predicting Bank Distress in the UK with Machine Learning (Suss, Treitel) Looks at the benefits of machine learning techniques for providing regulators with a warning of firm distress. This gave an approach that is better aligned to help intervene ahead of failure.
Refining the Workhorse Oil Market Model (Zhou) Paper makes adjustments to previous work which has a model considered as the go-to for analysis of global oil markets. The 5 refinements he tries had no effect on the substantive conclusions made – so the original model is still the one to use.
Value, Momentum and Carry – Is It Time for Equity Investors to Switch? (In the Long Run) For the active investors, value factors may offer a better risk reward profile, but, given the individual stock volatility dispersion, a market neutral defensive factor model, along the lines proposed by AQR, may deliver the best risk adjusted return of all.
A number of insightful pieces exploring how tech and machine learning in particular are breaking into finance. But models aren’t always perfect – mispricing risk can lead to a chain reaction and a downturn.
World Wide Currency (VOX EU) Is it possible to introduce a globally recognised electronic currency in the future alongside the national currencies? Researchers test this idea with a two-country model and conclude that it’s theoretically doable. Although for monetary policymakers, there’s certainly so much more to do to get them prepared for this futuristic trend.
A Volatility Smile-Based Uncertainty Index (Central Bank of Brazil) Introduces a new index to measure uncertainty: the “Volatility Smile-Based Uncertainty” (VSU). It looks at the discrepancy of the implied volatility of exchange rate options, and after calculating this value for five major emerging economies, concludes that VSU is negatively associated with industrial production and has peaks close to turbulent periods.
Ten Applications of Financial Machine Learning (SSRN/Cornell University) Explores how the core of machine learning – studying past data to predict future outcomes – can be revolutionary for the financial services industry. However, it also warns that machine learning tools are vulnerable to input selection biases and that can lead to undesired consequences.
Perceiving Risk Wrong: What Happens When Markets Misprice Risk? (Bank Underground) Risk perceptions are extremely subjective and hard to quantify. This paper examines how overpricing and underpricing market risks can both eventually lead to an economic downturn in the manner of a chain reaction.
FinTech, BigTech, and the Future of Banks (NBER) Explores areas in which non-bank fintech firms can outplay their banking rivals. Being less regulated than banks gives fintech firms an important competitive advantage. Large tech firms are also challenging traditional banking businesses such as consumer finance and loans due to their capability to tap into large amounts of unique user data.
Collateralized Loan Obligations in the Financial Accounts of the United States (Fed) Two new data series on CLOs have been introduced into US Financial accounts. The blog also describes how to navigate the tables to find these series and others relating to CLOs
Derivatives Trading in OTC Markets Soars (BIS) Latest triennial survey shows daily turnover in FX and rates derivatives has jumped from $11 trillion to 2016 to $19 trillion this year. The share of trading exchanges has also fallen.
Tracking the Sources of Robust Payments Growth: McKinsey Global Payments Report (McKinsey) Deep dive on payments landscape by region and player (including non-bank ones). Asia-Pac is the largest region by revenue.
Why Private Equity Is Ripe for Vanguard-Style Disruption (Institutional Investor) Argues that the average 7% fees for private equity is ripe for disruption. A Warren Buffet-style passive approach to holding private companies could be one path for this.
John C Williams: LIBOR – the Clock is Ticking (BIS) NY Fed President argues that market participants are not prepared enough for the end of LIBOR. Despite mentioning recent repo turmoil, he didn’t draw any connections between LIBOR reform and repo (there are some linkages)
Two great papers – one on modelling retail sales in almost real time and another on imperfect decision making.
From Transactions Data to Economic Statistics: Constructing Real-time, High-frequency, Geographic Measures of Consumer Spending (Federal Reserve) They find that daily retail transaction data from First Data Merchant Services can replicate monthly official retail sales data in almost real-time.
Modeling Imprecision in Perception, Valuation and Choice (Columbia, Michael Woodford) A piece on imprecise decision. It gives a summary of psychophysics which models the relationship between objective physical properties of a person’s environment and the way these are subjectively perceived.
Entrepreneurial Personalities (VOX) Finds that entrepreneurs have a higher tolerance for risk, stronger self-belief, sense of controlling one’s destiny and need for achievement than nono-founding CEOs, inventor employees and other employees.
New Index Tracks Trade Uncertainty Across the Globe (IMF) The Fund creates trade uncertainty indices for 143 countries starting in 1996.
Why We Should Care About Economic Uncertainty (Econlife) Describes some uncertainty indices and where to find them. They do impact growth.
Puzzling Exchange Rate Dynamics and Delayed Portfolio Adjustment (VOX) In theory, FX carry trades shouldn’t make money, so many ideas have emerged to explain this puzzle. This column argues that the slow response of investors to interest rate changes is the answer.
Predicting Returns with Text Data (Ke, Kelly, Xiu, working paper) Outlines single stock trading strategy around text-mining newswires. The daily models deliver sharpe ratio of between and 1 and 2 (after t-costs). Impressive stats.
Replacing LIBOR (Money and Banking, 8 min read) LIBOR will cease at the end of 2021. This piece raises concerns around the lack of clarity around how many contracts referencing LIBOR have fallback language for the switch. Could pose a systemic risk at some point.
3 Shockers from Yesterday’s RPI Plans (M&G investments, 2 min read) UK inflation-linked bonds will soon RPI inflation measure to the CPI measure. Biggest shocker is that linkers maturing beyond 2030 are at risk of having RPI calculations changed at the discretion of statisticians not the Chancellor.
Satellite Data Economics, Night Lights, and More (Conversable Economist, 3 min read) Useful blog that touches on and contains references on how satellite data can be used to measure growth.
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