The Leading Indicators: A Short History of the Numbers That Rule Our World

by Zachary Karabell

We are bombarded every day with numbers that tell us how we are doing, whether the economy is growing or shrinking, whether the future looks bright or dim. Gross national product, balance of trade, unemployment, inflation, and consumer confidence guide our actions, yet few of us know where these numbers come from, what they mean, or why they rule our world.
In "The Leading Indicators," Zachary Karabell tells the fascinating history of these indicators. They were invented in the mid-twentieth century to address the urgent challenges of the Great Depression, World War II, and the Cold War. They were rough measures-- designed to give clarity in a data-parched world that was made up of centralized, industrial nations--yet we still rely on them today.
We live in a world shaped by information technology and the borderless flow of capital and goods. When we follow a 1950s road map for a twenty-first-century world, we shouldn't be surprised if we get lost.
What is urgently needed, Karabell makes clear, is not that we invent a new set of numbers but that we tap into the thriving data revolution, which offers unparalleled access to the information we need. Companies should not base their business plans on GDP projections; individuals should not decide whether to buy a home or get a degree based on the national unemployment rate. If you want to buy a home, look for a job, start a company, or run a business, you should find your own indicators. National housing figures don't matter; local ones do. You can find them at the click of a button. Personal, made-to-order indicators will meet our needs today, and the revolution is well underway. We need only to join it.

Genres: Economics, Nonfiction, History, Finance, Politics, Mathematics, Money

304 pages, Paperback

First published February 1, 2014

About the author

Zachary Karabell is a New York-born author, columnist and investor who previously served as Head of Global Strategies at Envestnet, a publicly traded financial services firm. He currently hosts the podcast “What Could Go Right?” and analyzes economic and political trends as president of River Twice Research.

Reviews

[Steven Bragg · Rating 3 out of 5]

The concept is interesting, but the treatment is not concise. The main points of the book have been covered by the halfway point, after which the author diverges into alternative systems and recommendations - and the writing becomes more turgid. Reading about 100 pages into the text will provide the reader with most of the salient points.

[Raghu Nathan · Rating 5 out of 5]

Across the world, and in particular the Western world, it has become accepted practice among the general public to use indicators like the GDP, the unemployment rate, inflation percentage, trade deficit etc to understand and define the health of a nation’s economy and well-being. There is this belief that these numbers reflect reality accurately and help us to formulate future course of action. This book shows that these numbers were designed for a world in the mid-twentieth century and are increasingly unreliable for a Globalized world of commerce in the early twenty-first century. The author says that the belief that the complexity of today’s national and global economic systems can be captured using a few concise numbers, averages and percentages is a myth and should be done away with. Instead, what we need to do is to embrace the information age fully and find out which questions actually need to be answered and find ways to answer them satisfactorily.

The book traces the history of many of the major indicators, in particular the GDP, unemployment rate, inflation and trade deficit and why they came about in the first place. Then, it goes on to show why many of these indicators is flawed in today’s world. I particularly liked the discussion on GDP and trade deficit. It was really a shock to me to learn that the immensely popular iPhone and iPad of Apple do not figure in the GDP or the GNP of the US at all! The reason is that these products are manufactured outside the US in China by a Taiwanese contractor, Foxconn. Consequently, iPhones and iPads are shown as imports from China and accounted for as ‘trade deficits between the US and China’to the tune of billions of dollars!

Other GDP anomalies are as follows:
If a factory produces a product and creates significant pollution in the process, the product’s value, the cost of cleaning up the pollution and the resultant health care costs of the workers affected by the pollution are all positives for the GDP. On the other hand, if I sit at my computer desk and search using google and find the best hotel in Berlin for my holidays without running from one travel agent to another or making a number of telephone calls to hotels, such efficiency gains are actually a negative for the GDP! To drive home the point more forcefully,, GNP includes air pollution, cigarette advertising, special locks on doors, destruction of redwoods, nuclear warheads and TV programs which glorify violence. It does not include health of our children, quality of education, integrity of public officials or our compassion. In fact , everything except what makes life worthwhile!

Let us turn to trade deficit. We constantly hear on both sides of the political aisle that our trade deficit with China is constantly increasing and it is due to China manipulating its currency and using unfair trade practices. This book shows that if we look deeper into this question, it would emerge that there is probably no deficit at all and in fact, the truth may be the other way around! Consider the iPhone and the iPad again. The globalized supply chain means that in the iPhone, the camera is actually the output of Infineon, a German firm. The touch screen display is manufactured by the Japanese firm, Toshiba. The Bluetooth Wifi chip is from the Silicon Valley firm, Broadcom. The iPhone itself is only assembled in China, that too in the Foxconn factory, a Taiwanese contractor. Out of a total value of a $249 iPhone, only about $10 worth of business seems to go to China, mainly as salaries to workers in the Foxconn factory! (The full picture is even more complicated because Infineon, Toshiba and Broadcom in turn may have sourced the components for their camera, display and the chip from many different places, including China). But, the entire $249 is shown as US trade deficit against China. The author says that this is a telling example of how our indicators aren’t keeping pace with the globalized manufacturing world.

So, what can be done to get a more accurate picture of the state of the world? The author talks about the Human Development Index (HDI) suggested by Nobel Laureates Joseph Stiglitz and Amartya Sen, which depends on life expectancy, infant mortality, literacy, education levels, health, diet, gender differences, urban and rural differences, rich and poor differences, etc. This is more suited to evaluating developing nations more accurately but suffers from the problem that countries are asked to report their numbers on these themselves and so they can fudge them to make themselves look good. Yet another approach is to define a ‘Happiness Index’, which was tried in the Himalayan kingdom of Bhutan.

In conclusion, the author says that in a world where anyone with a smartphone can access infinitely more data than what the specialized statisticians could in 1950, it is absurd to depend on the indicators defined in that era to navigate the world today. Instead, Governments must make productive use of ‘Big Data’ and define bespoke indicators themselves for tailoring policies more accurately. For example, economic policies must account for CPI in differing parts of a country instead of one number for the entire country. Even though it may be difficult in a democracy to do this, Big Data technology makes such bespoke numbers possible thereby making governance more receptive.

I loved reading this book and found it extremely educational. It provided me a platform to step back a bit and view the larger picture of the assumptions we make instead of getting carried away by the media-hype on the various statistical indicators which tell us how our lives are going. It is important to reiterate the message that these myriad indicators are only a guide to comprehending reality and not Reality itself. This is not only true of these economic indicators but also true of many other numbers which substitute for the actual thing in other fields as well.

[Kay · Rating 2 out of 5]

This is a totally interesting exploration of the many factors we use to measure the health of the economy. Karabell seriously takes a look at the main measures we take as gospel in today's picture of the overall economy -- CPI, unemployment, GDP and more. Many of them are inventions that are less than a century old. All of them are deeply flawed.

Much of the way we frame modern news and interpretation of economic growth is heavily shaped by these numbers, yet few people have a thorough understanding of the measures or their shortcomings. While we have come a long way since the first attempt at measuring an economy -- called The Domesday Book -- I came away realizing that many of the measures, though a million times more statistically sound than that initial count, still don't give us a completely accurate count of what's happening.

More disheartening, these measures lead people to make proclamations that are sure to be disproven, like that no president has been re-elected while unemployment was above X percent. But what employment numbers mean have changed dramatically since they have been invented. In the middle of the 20th century, around the time the measure became popularized, a good chunk of adult women weren't working -- and women of color were working but not at jobs that could be measured by employment statistics. This has changed dramatically over time. Karabell makes note of these major structural employment changes, such as the mystery of why inflation stayed low in the 1990s, when employment was so high, because other economic forces like increased productivity are at work.

Now, many economists will say that although the unemployment numbers are slowly shrinking, the number people without jobs remains high, with more and more people simply dropping out of the workforce and simply giving up on having jobs. Karabell points out that the very measure of unemployment is rather fuzzy. What does it mean to be employed or unemployed? What does it mean to be looking for a job? Lots of people aren't earning money actively, but might pick up side work that doesn't necessarily count toward the total employment picture. Many aren't finding jobs that are "worth it" so drop out of the workforce, but may work again for the right kind of work.

All of these things just show how, no matter how smart the statisticians working on measuring the economy are, we may never see an "accurate" picture of the increasingly complex economy.

[Omar · Rating 4 out of 5]

Clearly and well written. Thought-provoking for folks who may not have questioned GDP before (Did you know? GDP became standard in the US only in 1991; prior to that Gross National Product was the leading indicator). Because the author offers a nuanced cadence the whole time, the book fails to push the reader to really embrace 'bespoke' indicators as a wholesale solution, but it does set the stage for more exploration.

[Charlie Cray · Rating 4 out of 5]

Good, very accessible and insightful history of key economic indicators.

How and why were the GDP and GNP created? If you want to know, this is a good place to start.

As we all know (and RFK famously described) -- what matters is what's measured, and economic indicators like GDP leave out of a lot of what we now value as essential and include as positive contributions to the national economy things that are hugely destructive.

But when it was created during the Great Depression, the GDP (along with the national employment index) was a useful guidepost to policy makers who didn't fetishize it the way it later came to be.

It had its inherent biases built in from the start, even if they weren't intentional. E.g. GDP doesn't account for domestic work, including cleaning, caring for children, etc. No one argued in the 1930s that domestic work was anything but central to well-being - but it was still left out of the GDP because this work was unpaid and therefore not easy to measure.

At this point, GDP is largely too simple and obsolete an indicator to matter to most of us. For small businesses, and individuals, it's largely irrelevant to key decisions we make. For large multinationals, the GDP may be a general guidepost, but doesn't provide any intel on specific sectors that might provide for strategic insights. Each major corporation is its own economy and must track and weight different data specifically relevant to its line of business, geographic reach (and aspiration). It needs to track key competitors, the price of key material inputs, emerging political, economic and other risks. This all gets very sophisticated very quickly, which is why many corporations have a chief economist.

Now, in the age of Big Data, many companies will follow the model of leading hedge funds and establish their own trading departments (especially useful when you receive information from physical operations that might affect markets before the broader public does).

But for most of us, the key macroeconomic indicators like GDP and mortgage rates or unemployment (even for those looking for a job) are irrelevant or largely useless. We do our own research. Nevertheless, we still get bombarded with news about these and other numbers and the consequences seep into our psyches. There is a link between sentiment and behavior. Fear of inflation affects how we shop; what people believe about the state of the economy intimately shapes their spending decisions.

The problem is that without a nuanced understanding it's easy for things to get distorted. Companies that tether capital spending to inflation numbers may find themselves underinvesting in the future. That's on top of other factors that have incentivized "short-termism": In "The Number," Alex Berenson pointed to two developments in the 1990s that reinforce corporate myopia: the regulatory changes that allowed companies to pay top executives' salaries in stock options, (which created an incentive to juice share prices as we later saw with companies that cooked their books); the other was cable TV's 24-hour reporting on markets and business news.

GDP is just one of many indicators and over time others were developed and instituionalized at the BLS, BES, Conference Board (Consumer Confidence Index), Bureau of Economic Analysis at the Commerce Dept, Federal Reserve and others. All served to define "the economy" in their own ways. Other more obscure ones include the National Association of Purchasing Agents survey of business conditions (ISM).

As the economy became more global and comparisons between West and East, and concerns about development strategies grew, the UN, the World Bank and the IMF also became important sources for macroeconomic stats. But for the most part they rely on what national governments provide.

The gaps between major indicators like GDP and the complexities of the economy are underscored by the emergence of widespread availability of scores of different types of data readily available at our fingertips. We see GDP as a kind of joke, but it still has a certain drag-anchor effect on policymaking today.

In the 1930s, policies were creative and innovative by default: There was little legacy of governments attempting to ameliorate systemic economic issues using data and statistics. These indicators were developed to help those policymakers navigate the many and varied experiments.

Today, the lead indicators are not used that way. Instead, our national statistics often act as "barriers to innovative approaches rather than facilitating them. The congressional straightjacket that forces the CBO to project growth rates is a high barrier to investing in the future," Karedell writes. And budget restraints make it hard to update old indicators, let alone invent new ones.

So that what we need is not an alternative set of equally limited indicators, but indicators tailored to our particular needs, or to specific policy questions.

Innovations have occurred - largely elsewhere. There's a chapter on Bhutan's happiness index, which also points out that President Sarkozy of France charged a commission to come up with a new way to measure the economy. They came up with a "dashboard" approach that expands the array of statistics used in determining policy.

Karabell points out that the Federal Reserve does that too. And within the Bureau of Economic Analysis there are already multiple variants of inflation and price deflators. Within the BLS there are half a dozen established alternative unemployment measures. The ideas are there. What's the problem?

Like so many other problems, the ossification of American economic policy discourse can at least in part be attributed to a lack of political leadership, particularly a woefully dysfunctional and indifferent Congress that has pared back its own expertise (including committee staff), along with the limited resources provided to the CBO, the Congressional Research Service and other sources of potential expertise (Congress could create its own center for data analysis, modeled along the Office of Technology Assessment - which should be reincarnated - but they'd have to be insulated by design from political pressure).

The world won't wait. Statistical innovations are coming rapidly, from all sorts of places, including businesses, academia and collective groups of people meeting in online chat rooms, where they crowdsource ideas and answer difficult questions.

In the age of ubiquitous and widely available Big Data, smart meters, etc. - local governments are doing some interesting things, too.

Some of the uses of Data of course raise other questions. But that's a topic for another book (see "Surveillance Capitalism"). If you're into data, you might check this book out. It's most valuable for a historical perspective but it will also confirm any creative person's thirst for better metrics and information to describe the crazy, rapidly changing, and complicated realities of the world we live in.

[Jeffrey · Rating 3 out of 5]

The Leading Indicators gives a good account of the history and the people behind some of the statistics that we come to rely on today. It's message though should be familiar to anyone that deals with data - you can only obtain answers for what you seek to measure. That insight is not new - however there is some insight provided into why the indicators were constructed as they were.

The last part of the book feels unnecessarily long - the penultimate chapter involves Karabell telling us in about 1000 permutations that Bhutan has struck its own math in measuring happiness rather than GDP. The last chapter is interesting in that it provides some glimpse into alternatives, but here detail is scant. Finally his conclusion is that everyone should use Google to find their own relevant information or data - a message that is probably obvious.

In short - the book is OK and a good introduction to the indicators. But the reader will need to do much more work, but any reader familiar with data would know that already.

[Fred Cheyunski · Rating 4 out of 5]

Current Gauges and Tailoring New Measures - I was attracted to this book since an interest of mine is looking at ways we gauge our current situation and the ways our human condition is progressing. In his 11 chapters, author Karabell provides an revealing account of the various measures that have become so dominant in modern life such as Gross Domestic Product (GDP), Unemployment, and Inflation. He makes the case that these metrics were designed to address particular questions, where we now often look for broader answers.

Names of some of those associated with the rise of indicators include William the Conqueror and the Domesday Book from 1086, Napoleon and La Place with his A Philosophical Essay on Probabilities 1795, Hamilton’s Report on Manufacturers in 1791, Ethelbert Stewart(Bureau of Labor Statistics) work on Unemployment starting around 1930, Simon Kuznets’ (National Bureau of Economic Research) Income Accounts/GNP/GDP from 1930, Arthur Burns & Wesley Mitchell (NBER) Measuring Business Cycles beginning in 1946, as well as Irving Fisher’s (NBER) Consumer Price Index/Inflation dating from that time.

Then there are George Katona (University of Michigan Survey Research Center) with his Consumer Confidence reports in the 1950’s & 60’s, the creation of the While House Office of Management & Budget/Congressional Budget Office in the 1970’s, the World Trade Organization Rules of Origin in the 1980’s, and the UN Human Development Report originating in the 1990’s.

More recently, Erik Brynjolffson, Andrew McAffee, Joo Hee Oh (MIT) GDP have critiqued how typical measures are not keeping up with technological development. The notion of Consumer Surplus has arisen with preliminary findings that internet tools have added as much as $34 billion a year to consumer surplus between 2002 and 2011, a number that has undoubtedly increased in the years since. In 2013, the Bureau of Economic Analysis (BEA) added revisions to GDP going back to 1929 to include” intangible assets” [e.g. services, intellectual property, R&D etc.].

Karabell covers all these developments and brings in other more recent voices to advocate tailoring and use of available indicators as well as the rise of Big Data to move forward in getting information needed for the queries we have. He alludes to people such as epidemiologist Hans Rolling with his highly visual Gapminder, Nate Silver with his statistical models applied to polling, and hedge fund investor Ray Dalio with his particular approach as examples.

Along with books such as Sharma’s “Rise and Fall of Nations,” Khanna’s “Connectography,” Lanier’s “Who Owns the Future,” and Davenport’s “Keeping Up with the Quants,” Karabell provides a compelling argument for utilizing what we have available and getting “better handles” for dealing with aspects of world we face.

[Dave S · Rating 2 out of 5]

In a flashily titled book, the author laments how society puts too much faith in the standard economic indicators like unemployment, CPI, and GDP. While I was pleased to discover how these indicators came into forms (a study of statistics and probability, according to the author, were established in 18-19C), the author seems to underestimate the knowledge and prudence of his readers. In particular, he seems to have an issue with the 2012 presidential campaign where “no president has ever been reflected with an unemployment rate above 7.2 percent” was told routinely. One could easily spot an issue of “cause and effect” here, and I would not believe that Obama supporters were dissuaded by the unemployment rate to vote for him. If indeed the 7.2% narrative was told repeatedly by the media, it should’ve been one of these flashy attempts to attract readers’ attention, I would assume.

Limitations to the unemployment and GDP numbers in capturing what is happening in the real economy has often been discussed, and the author did not propose an alternative to how we should measure the health and well being of our economy.

I read the first two chapters, bored, skipped to the conclusion, and decided it was not worth my time to read the whole book

[Carlos · Rating 3 out of 5]

This was an interesting look at the development of the numbers that seemed to have always dominated the economy, like GDP, unemployment rate, inflation rate, etc., but that have only been around for less than a century. Karabell takes us to the decade leading up to the Great Depression and chronicles the radical notion of measuring the ebbs and flows of money in the whole country. He then narrates the gradual shift from inconspicuous numbers presented in dry reports to government agencies to the endlessly press-covered “leading indicators” that people use to predict everything from presidential elections to car purchases. In this way he buttresses his argument for the wildly unnatural use of these numbers, especially considering how and when they were created. Karabell also shows how an ever-growing number of skeptics have started to look for alternatives to replace or supplement these numbers running the gamut from Bhutan’s Gross National Happiness to the UN’s Human Development Index. While not exactly riveting Karabell does manage to make the reader think more critically about what these numbers say and what they don’t.

[Deepanshu Gupta · Rating 4 out of 5]

The author has combined the brief history of regularly reported numbers and statistics like GDP, GNP, GNI etc. These numbers were formed out of the necessity of stray federal policies and their effects. A metric was needed to assess the effects of various policy decisions and their effect on national economics at micro and macro level. Although revered at the inception when US economy was dominated by War and Machinery manufacturing, these numbers have lagged in time with changing technological development. Numbers like Unemployment index are not sufficient for the free lancing population, statistics such as GDP(in their original form) cannot take into account the value created by software and intangible products. Overall this is a wonderful book for anyone interested in knowing about how these life-governing numbers came into existence. Personally I feel governments have done a lazy job at not analysing their own metric statistics for policy analysis and taken for granted numbers that were made for a World War and Depression era.

[Tad · Rating 2 out of 5]

The central thesis of The Leading Indicators is important - the headline numbers we use to understand our economy are in many ways outdated and relied upon much more heavily than can be justified. However, this argument could have been made in a much shorter book, or even an essay, and ends up being repeated many, many times without much added value. Furthermore, the follow-up question, what should we do about it, is given a pretty skimpy and superficial treatment. Karabell's answer seems to be that every person and every company should set up their own Google Sheets document to track numbers relevant to their lives instead of looking at headline employment, inflation, and GDP numbers. This might be good advice for some, and is something that most large businesses have already been doing for a while I would imagine, but is unrealistic for most individuals and doesn't seem to really address the problem of how 'the leading indicators' function totemically in our society. I would have liked to see a fuller, more thought-out argument about where we go from here.

[Patrick · Rating 3 out of 5]

Not a classic because very journalistic in feel, but a genuinely helpful book to someone not intimate with these numbers already. A good complement to Damned Lies and Statistics, by Best. Along the same vein, showing the weaknesses of these numbers and encouraging more skepticism in the use of them. The history was appreciated, too, but might be supplemented by more sources. He has a definite viewpoint, which actually gave the book more value for me. On the whole, very readable and interesting to someone not deeply into economics already. I could read a half dozen more books like this about different aspects of statistics at this reading level. Like I've said, not a book for economics majors but very helpful to the general public.

[Paul · Rating 3 out of 5]

Karabell offers a history of the economic indicators we use to determine the health of our economy and a well thought out argument as to why there were never meant to be used the way they are know. The book is lively and pitched solidly towards the layman. It's a fun, interesting read about a subject that makes most people's eyes gloss over.

[Mike · Rating 5 out of 5]

I have read scores of books on economics and found this to be a great addition. For those who don't understand much economics it is a well-written and easy to digest look at the big numbers that are constantly in the news; for those experienced in economics there are new stories here and different perspectives often missed. A great job and recommended.

[Dan · Rating 3 out of 5]

An exhausting review that tells the reader that every economic indicator has many faults. So in a sense, there are no leading economic indicators. But wait, I can go the author one better by just using the S&P 500 index on the New York stock exchange. At least this index tells you the basic health of the United States economy. It approximately doubled over eight years of the Obama years and has already risen by about 50 percent in less than two years during the Trump presidency.

[Nathan · Rating 3 out of 5]

I was a little disappointed by this book. I was ready to nerd out about some statistics, but this book recycles the same points over and over, and I feel like I pulled very little from this. Honestly, besides the history of how GDP and inflation came to be, most of this book is written as common sense that we shouldn't use broad indicators to judge individual parts of society.

[Dave Wallace · Rating 4 out of 5]

How our economy is measured and planned, it will scare the crap out of you to find out the data analysis is so incomplete and flawed.

[Luis · Rating 4 out of 5]

While the book aims to tackle the often debated question of the value of happiness in society, it is not well packed with cognitive psychology theory to make of those attempts serious ones. However, despite this drawback, the book does an excellent job at exploring the gap between what economic indicators express and the actual economic experience of members of society. The book also does a great job at exploring the lives of those involved in the creation of such indicators. Great book for anyone interested in better utilizing data to make decisions.

[Paul W · Rating 4 out of 5]

Was interesting, and I had little knowledge of these numbers beforehand. Hopefully I will retain some of the info but probably not

[S · Rating 3 out of 5]

I'm confused with two different conflicting messages in the book. The book starts with the message that the leading indicators are too fresh to get such importance in our daily lives - citing several times that they are just 50+ years old. Something that's just that amount of small history shouldn't drive what nations do. And then it ends with why these indicators are not as useful in real life, how they miss out some aspects on our economic lives and how they need to be updated for today's world. Suggesting they are Good enough and we should discard the headline numbers and use them only in context. On one hand suggesting they need to more matured and just 50 years young and on other hand suggesting they should discarded and should be started over.

Also it's definitely long winded. Lot of points and concepts could be made concisely with less text. Many times throughout the book the same rhetoric is repeated numerous times. Better approach would be starting it with the gist and then explaining it in detail or explaining the details and revealing the gist with final conclusion.

Liked the historic anecdote behind each leading indicator but the whole book lacks substance. Neither does it explain scientifically what these numbers represent and how they are used precisely with examples and methodologies used to calculate them etc. not does it do any justice explaining them theoretically. What it rather does is gives some historical background and then debates it's usefulness, the only part that's covered well is who's who and names of people who got it all started.

I was expecting more but alas it was a good read. I learnt few things I didn't know before reading the book.

[Kate · Rating 5 out of 5]

I won a copy of this book through Goodreads, and Karabell's book far exceeded my expectations. The Leading Indicators: A Short History of the Numbers that Ruled Our World is a must read book for anyone who is concerned about the economy. Karabell addresses concerns regarding the methodolgy statisticians use to quantify the economy. Often, statisticians calculations do not gauge the experience of people and businesses. Karabell is a brilliant writer and outstanding researcher! Before reading this book, I had never heard the quote from Robert Kennedy on GDP which states, "too much and too long, we seem to have surrendered community excellence and community values in the mere accumulation of material things. Our gross national product ... if we should judge America by that - counts air pollution and cigarette advertising, and ambulances to clear our highways of carnage. It counts special locks for our doors and the jails for those who break them. It counts the destruction of our redwoods and the loss of our natural wonder in chaotic sprawl. It counts napalm and the cost of a nuclear warhead, and armored cars for police who fight riots in our streets. It counts Whitman's rifle and Speck's knife, and the television programs which glorify violence in order to sell toys to our children.
Yet the gross national product does not allow for the health of our children, the quality of their education, or the joy of their play. It does not include the beauty of our poetry or the strength of our marriages; the intelligence of our public debate or the integrity of our public officials. It measures neither our wit nor our courage; neither our wisdom nor our learning; neither our compassion nor our devotion to our country; it measures everything, in short, except that which makes life worthwhile. And it tells us everything about America except why we are proud that we are Americans." I found Kennedy's quote to be very helpful in understanding how our economic indicators have limitations.

[Rick Taylor · Rating 5 out of 5]

The Leading Indicators is a fascinating history of economic gages such as the GDP, inflation rate and unemployment rate. A must read for economics, business and statistics nerds. The reasons why the statistics were created and the people behind them make for a great read. Before the 20th century, there was no reliable data to assess the “economy”. At the start of the Great Depression, there weren’t solid statistics that could pinpoint the actual condition of the economy. There were endless antidotal stories of business closures and unemployment, but nothing concrete for the government to determine whether things were on the upswing, getting worse, and what interventions work, etc. From the 1930s on, the federal government, UN, Fed and other organizations started surveying and tracking economic data. This is the meat of the book. The author goes on to point out weaknesses in the various indicators and offers recommendations for improvements. Interesting, but for me, the story of how each leading indicator was developed and used since the depression makes this book a remarkable achievement and one well worth exploring.

[Todd · Rating 3 out of 5]

Karabell makes a very important point in this book, exploring persuasively how economic measurements with their roots in the Great Depression no longer measure economic activity in a useful manner and can create false perceptions. The history of the visionary government statisticians was great to read, especially as someone who does performance measurement for the government for a living.

My biggest criticism is probably more appropriately directed at the editor rather than Karabell himself. The book devolves into repetition and tedium in the second half, as Karabell makes the same points repeatedly with little new insight or information as it progresses. This would have been a four star if about 30 pages of filler was trimmed out. It's not a serious enough sin for me to take away my recommendation, but if you put it down 2/3 in and don't find your way back, you won't have missed much.

[Rich · Rating 3 out of 5]

A bit dry

The book starts out well giving you the history of major economic statistics and how it came about. The author does a fine job in the department but a majority of the book is focused on why those numbers should not carry the significance they now do.

He does a great job of stating his case and I agree with him 100% but he gets a bit wordy. In fact, I will describe it as word barf. He could of made his point in half the amount of words that he actually used.

All in all, it was an interesting read. I would suggest this book to anyone who has an understanding of major macroeconomic indicators, but just plan on being frustrated with author continually repeating things already covered. But, inside all that word barf I promise there is gems of knowledge and new perspectives on the statistical collection in Economics.

[Christine · Rating 5 out of 5]

I won this book through Good reads. I have always been skeptical of the media in general, especially the way the talking heads use statistics to measure the days leading indicators to arrive at so called accurate conclusions. The educated personalities in the media introduce the information in such a confident manner and they attempt to convince us that information is infallible and has been accurately collected for generations. I am happy to learn that my skepticism of the media is still justified. This was an excellent book for me because I like to know whats really going on. What makes this book so good is that an uneducated person can fully understand a very complex topic when written by Zachary Karabell.

[victor harris · Rating 4 out of 5]

Makes an excellent case that our key economic indicators which have so much impact on policy making are hopelessly outdated. GDP, inflation, unemployment are all markers that still carry immense influence but do not realistically address a modern world of globalization, transnational corporations, and a electro-digital world. He supplies innovative alternatives that may offer better gauges of 21st century economics. Quite readable with the only downside being it was a little repetitive in stressing how anachronistic the traditional economic indicators are. Nevertheless, still informative and thought-provoking.

[Josh Gunter · Rating 3 out of 5]

This book will be too simplistic for anyone who's taken introductory Econ. courses, but the author's overall point is interesting: national economic statistics contain far less insight into the "real" economy than we think they do, and they're even less helpful for navigating our personal economic lives. The author advocates building your own set of "bespoke" indicators, but is short on examples of how to actually do this.

Read this if you're looking for a broad, non-technical introduction into economic statistics. It's lively and quick, but if you already know a thing or two, look elsewhere.

[Avrohom Kotler · Rating 5 out of 5]

Gives the history of the origins of the big numbers that are used as metrics for the economy. Like the unemployment rate and inflation (CPI Consumer Price Index). Karabell argues that while at the time of creation these numbers were meaningful, they are much less so today. Too many details are glossed over in 1 big number & large geographic area dilutes it's meaning. What is accurate for NYC is not accurate for suburban Kansas. This book has positively impacted my understanding of Macroeconomics.

He ends by saying one needs to look at local & more detailed numbers to make decisions, but is short on how to do so.

[Luke Alonso · Rating 3 out of 5]

I very much enjoyed the historical parts of the book. Our statistical indicators were each purpose built to meet a specific need and are now used outside of that original purpose. This is the fate of most statistics in business as well as government. The circumstances and development of our indicators was fascinating, but later sections don't offer many alternatives or ways to avoid the inevitable obsolescence of statistical measures.

[Justin Time · Rating 4 out of 5]

Great book! Its sort of the equivalent to the matrix of current economics. Its the red pill! This is a great place to start if you 2nd guess the numbers that you hear every day and especially if you 2nd guess their interpretations. If you are already familiar with the flaws in things like the trade deficit or GDP, you might not be too surprised.Perhaps, you already took the red pill!