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In this article, it exemplifies how evaluating the economic impact of summer has much in common with attempts to measure the effects of major events. Stores and shops swap out their products depending on the weather that's approaching. Similar to how holidays are decorated, companies document the time intervals for consumers to purchase accordingly. Seasons play a major role when the most polarizing weathers, winter and summer, are near.
I predict prices will change in the real world market because if it's winter, it's mandatory for coats to be worn and consumers would pay any reasonable amount for it. When it changes to spring, prices for winter attire will decrease because people no longer need to keep warm in such temperatures anymore.

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The Office for National Statistics has produced a report on sales of popular summer-related products. Official data on sales of goods are limited in that they tend to be based on annual spending, but clearly the demand for some products tends to be seasonal. Various cold drinks, meat (for barbecues) and ice cream are identified as typical examples.

While we do not have official data on the extent to which demand for these goods varies over the year, unofficial data allow us to learn a little more about the extent to which a good (or a bad) summer can affect demand.

A major UK ice cream producer reports that some 68% of its revenue is earned in the second and third quarters of the year. Using this figure alongside typical monthly temperatures in the UK allows us to establish that a 1% increase in temperature results in a 1.2% rise in the demand for ice cream. An August in which temperatures are one degree hotter than usual therefore likely results in a 6% increase in ice cream sales during that month.

Office for National Statistics

Data from Information Resources Inc compare UK demand for cold alcoholic drinks in the two week period to July 20 2013 with that of the corresponding period in the previous year. Data on temperatures near the geographic centre of the UK for these periods indicate that, in 2013, the average was 20.6°C, while in 2012 it was just 15.7°C.

Office for National Statistics

Of course, other factors - especially economic factors - are likely to affect demand too. Abstracting from these, however, a 1% increase in temperature seems to be associated with an increase in demand of around 2.4%. An August in which temperatures are 1°C hotter than usual would therefore lead to an increase in demand of around 12%. This should be regarded as an upper bound in view of the fact that some of the increase in demand between 2012 and 2013 might have been due to changes in general economic conditions rather than changes in temperature.

The analysis of seasonal effects is particularly difficult in the case of meat, not least because different types of meat are popular at different times of the year. The demand for sirloin may be relatively high in the summer, but the demand for roasting joints is relatively low at that time of year. Overall, statistics on meat production do not indicate any substantial increase in the summer - indeed the peaks for sheep and pig meat come later in the year.

Other types of summer-related goods include garden furniture, barbecues and air conditioners. But since these are durable goods, consumers benefit from them over the course of several summers, some of which will be hotter than others. We would expect people to average out across several years their likely use of these products, and so purchases of such goods should not be unduly sensitive to a heatwave in any one year.

Evaluating the economic impact of summer has much in common with attempts to measure the effects of major events. Typically the expenditure that is associated with an event (be it the Olympics or a heatwave) is diverted rather than created - and it matters where it is diverted from and where it is diverted to. If we spend more on beer but less on coffee, the aggregate effect on the UK economy is likely to be small. If, however, we spend more on domestic holidays and less on going abroad to chase the sun, the economy will benefit.

As the above figures indicate, for the producers of at least some summer-related goods, a good summer can be good in more senses than one. But an important catch in all of this is that much of the increased expenditure on summer related products is mirrored by decreased spending on other things.

For every ice cream that is eaten, a hot chocolate may be eschewed. So - tempting as it might be to try and calculate a figure for the economic value of a hot summer - adding up extra sales revenues for these products is not really a particularly instructive exercise. Indeed, the true value of a summer is most likely captured by the feelgood factor that a little sunshine brings, so enjoy it while you can.

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Explainer: how does the weather affect the economy?

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The Office for National Statistics has produced a report on sales of popular summer-related products. Official data on sales of goods are limited in that they tend to be based on annual spending, but clearly the demand for some products tends to be seasonal.

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In this article, it exemplifies how tax rate cuts may encourage individuals to work, save, and invest, but if the tax cuts are not financed by immediate spending cuts, they will likely also result in an increased federal budget deficit, which in the long-term will reduce national saving and raise interest rates. Meaning, if taxes are relatively high, demands will decrease in goods and services. Taxes are detrimental if it's not paid off rightfully so people need to prioritize their money for it.
I predict prices will change in the real world market because if taxes become exceedingly high, low demands will affect company enterprises.

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Abstract

This paper examines how changes to the individual income tax affect long-term economic growth. The structure and financing of a tax change are critical to achieving economic growth. Tax rate cuts may encourage individuals to work, save, and invest, but if the tax cuts are not financed by immediate spending cuts, they will likely also result in an increased federal budget deficit, which in the long-term will reduce national saving and raise interest rates. The net impact on growth is uncertain, but many estimates suggest it is either small or negative. Base-broadening measures can eliminate the effect of tax rate cuts on budget deficits, but at the same time, they reduce the impact on labor supply, saving, and investment and thus reduce the direct impact on growth. They may also reallocate resources across sectors toward their highest-value economic use, resulting in increased efficiency and potentially raising the overall size of the economy. Results in the literature suggest that not all tax changes will have the same impact on growth. Reforms that improve incentives, reduce existing distortionary subsidies, avoid windfall gains, and avoid deficit financing will have more auspicious effects on the long-term size of the economy, but may also create trade-offs between equity and efficiency.

Introduction

Policy makers and researchers have long been interested in how potential changes to the personal income tax system affect the size of the overall economy. In 2014, for example, Representative Dave Camp (R-MI) proposed a sweeping reform to the income tax system that would reduce rates, greatly pare back subsidies in the tax code, and maintain revenue levels and the distribution of tax burdens across income classes (Committee on Ways and Means 2014).

In this paper, we focus on how tax changes affect economic growth. We focus on two types of tax changes - reductions in individual income tax rates and "income tax reform." We define the latter as changes that broaden the income tax base and reduce statutory income tax rates, but nonetheless maintain the overall revenue levels and the distribution of tax burdens implied by the current income system. Our focus is on individual income tax reform, leaving consideration of reforms to the corporate income tax (for which, see Toder and Viard 2014) and reforms that focus on consumption taxes for other analyses.

By "economic growth," we mean expansion of the supply side of the economy and of potential Gross Domestic Product (GDP). This expansion could be an increase in the annual growth rate, a one-time increase in the size of the economy that does not affect the future growth rate but puts the economy on a higher growth path, or both. Our focus on the supply side of the economy in the long run is in contrast to the short-term phenomenon, also called "economic growth," by which a boost in aggregate demand, in a slack economy, can raise GDP and help align actual GDP with potential GDP.

The importance of the topics addressed here derive from the income tax's central role in revenue generation, its impact on the distribution of after-tax income, and its effects on a wide variety of economic activities. The importance is only heightened by concerns about the long-term economic growth rate (Gordon 2016; Summers 2014) and concerns about the long-term fiscal status of the federal government (Auerbach and Gale 2016).

We find that, while there is no doubt that tax policy can influence economic choices, it is by no means obvious, on an ex ante basis, that tax rate cuts will ultimately lead to a larger economy in the long run. While rate cuts would raise the after-tax return to working, saving, and investing, they would also raise the after-tax income people receive from their current level of activities, which lessens their need to work, save, and invest. The first effect normally raises economic activity (through so-called substitution effects), while the second effect normally reduces it (through so-called income effects).

The financing of tax cuts significantly affects its impact on long-term growth. Tax cuts financed by immediate cuts in unproductive government spending could raise output, but tax cuts financed by reductions in government investment could reduce output. If they are not financed by spending cuts, tax cuts will lead to an increase in federal borrowing, which in turn, will reduce long-term growth. The historical evidence and simulation analyses suggest that tax cuts that are financed by debt for an extended period of time will have little positive impact on long-term growth and could reduce growth.

Tax reform is more complex, as it involves tax rate cuts as well as base-broadening changes. There is a theoretical presumption that such changes should raise the overall size of the economy in the long-term, though the effect and magnitude of the impact are subject to considerable uncertainty. One fact that often escapes unnoticed is that broadening the tax base by reducing or eliminating tax expenditures raises the effective tax rate that people and firms face and hence will operate, in that regard, in a direction opposite to rate cuts and mitigate their effects on economic growth. But base-broadening has the additional benefit of reallocating resources from sectors that are currently tax-preferred to sectors that have the highest economic (pre-tax) return, which should increase the overall size of the economy.

A fair assessment would conclude that well-designed tax policies have the potential to raise economic growth, but there are many stumbling blocks along the way and certainly no guarantee that all tax changes will improve economic performance. Given the various channels through which tax policy affects growth, a tax change will be more growth-inducing to the extent that it involves (i) large positive incentive (substitution) effects that encourage work, saving, and investment; (ii) small or negative income effects, including a careful targeting of tax cuts toward new economic activity, rather than providing windfall gains for previous activities; (iii) reductions in distortions across economic sectors and across different types of income and consumption; and (iv) minimal increases in, or reductions in, the budget deficit.

The remainder of the paper is organized as follows. Section II provides a conceptual framework by discussing the channels through which tax changes can affect economic performance, including the many ways in which a positive substitution effect in response to a tax rate cut might be dissipated or even reversed by other factors.

Section III provides an empirical starting point. We show that growth rates over long periods of time in the United States have not changed in tandem with the massive changes in the structure and revenue yield of the tax system that have occurred. We also report findings from Piketty, Saez and Stantcheva (2014) that, across advanced countries, even large changes in the top marginal income tax rate over time do not appear to be strongly correlated with rates of growth.

Section IV explores empirical evidence on taxes and growth from studies of major income tax changes in the United States. Consistent with the discussion in Section III, the studies find little evidence that tax cuts or tax reform since 1980 have impacted the long-term growth rate significantly.

Section V examines the new "narrative" approach to identifying tax changes that are exogenous to current economic conditions, stemming from the seminal work of Romer and Romer (2010). The literature, which generally uses vector autoregression (VAR) models, finds that tax cuts that meet the exogeneity criteria raise short-term output and other economic activity. The narrative literature does not speak to the long-term effects, though.

Section VI discusses the results from the literature on simulation models, which has generated two main results. First, debt-financed tax cuts will tend to boost short-term growth (as in standard Keynesian models and in the literature using the narrative approach), but also tend to reduce long-term growth, if they are financed eventually by higher taxes. Second, revenue-neutral income tax reform can provide a modest boost to economic growth.

Section VII concludes. ¹

[1] There are a number of related issues that are both interesting and important, but beyond the scope of the paper - including, for example, the elasticity of taxable income, the relationship between inequality (especially as it is affected by the tax system) and growth, the effects of corporate income tax reform on growth and the detailed literatures on the effects of taxes on labor supply, saving, and investment.

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Effects of Income Tax Changes on Economic Growth

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William Gale and Andrew Samwick examine how income tax changes can affect long-term economic growth and find that, contrary to conventional wisdom, there is no guarantee that tax rate cuts or tax reform will raise the long-term economic growth rate.

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In this article, it exemplifies when supply exceeds demand for a good or service, prices fall while demand exceeds supply, prices tend to rise. If a product is too expensive, companies objectively create substitutes to profit from it. Faking brands may plummet economically but food,, for example, can have alternatives that consumers may prefer more. Price controls or distorts an individual's willingness or ability to purchase a product so if there's substitutes that legitimately work at a lower price, people will take that opportunity.
I predict prices will change in the real world market because everyone wants to save instead of spending more than they should. Prices are crucial in economy for both buyers and sellers. So if prices of related goods are available, people will venture off instead of paying attention to the original product.

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The law of supply and demand is an economic theory that explains how supply and demand are related to each other and how that relationship affects the price of goods and services. It's a fundamental economic principle that when supply exceeds demand for a good or service, prices fall. When demand exceeds supply, prices tend to rise.

There is an inverse relationship between the supply and prices of goods and services when demand is unchanged. If there is an increase in supply for goods and services while demand remains the same, prices tend to fall to a lower equilibrium price and a higher equilibrium quantity of goods and services. If there is a decrease in supply of goods and services while demand remains the same, prices tend to rise to a higher equilibrium price and a lower quantity of goods and services.

The same inverse relationship holds for the demand for goods and services. However, when demand increases and supply remains the same, the higher demand leads to a higher equilibrium price and vice versa.

Supply and demand rise and fall until an equilibrium price is reached. For example, suppose a luxury car company sets the price of its new car model at $200,000. While the initial demand may be high, due to the company hyping and creating buzz for the car, most consumers are not willing to spend $200,000 for an auto. As a result, the sales of the new model quickly fall, creating an oversupply and driving down demand for the car. In response, the company reduces the price of the car to $150,000 to balance the supply and the demand for the car to reach an equilibrium price ultimately.

Increased prices typically result in lower demand, and demand increases generally lead to increased supply. However, the supply of different products responds to demand differently, with some products' demand being less sensitive to prices than others. Economists describe this sensitivity as price elasticity of demand; products with pricing sensitive to demand are said to be price elastic. Inelastic pricing indicates a weak price influence on demand. The law of demand still applies, but pricing is less forceful and therefore has a weaker impact on supply.

Price inelasticity of a product may be caused by the presence of more affordable alternatives in the market, or it may mean the product is considered nonessential by consumers. Rising prices will reduce demand if consumers are able to find substitutions, but have less of an impact on demand when alternatives are not available. Health care services, for example, have few substitutions, and demand remains strong even when prices increase.

While the laws of supply and demand act as a general guide to free markets, they are not the sole factors that affect conditions such as pricing and availability. These principles are merely spokes of a much larger wheel and, while extremely influential, they assume certain things: that consumers are fully educated on a product, and that there are no regulatory barriers in getting that product to them.

Public Perception

If consumer information about available supply is skewed, the resulting demand is affected as well. One example occurred immediately after the terrorist attacks in New York City on September 11, 2001. The public immediately became concerned about the future availability of oil. Some companies took advantage of this and temporarily raised their gas prices. There was no actual shortage, but the perception of one artificially increased the demand for gasoline, resulting in stations suddenly charging up to $5 a gallon for gas when the price had been less than $2 a day earlier.

Likewise, there may be a very high demand for a benefit that a particular product provides, but if the general public does not know about that item, the demand for the benefit does not impact the product's sales. If a product is struggling, the company that sells it often chooses to lower its price. The laws of supply and demand indicate that sales typically increase as a result of a price reduction - unless consumers are not aware of the reduction. The invisible hand of supply and demand economics does not function properly when public perception is incorrect.

Fettered Markets

Supply and demand also do not affect markets nearly as much when a monopoly exists. The U.S. government has passed laws to try to prevent a monopoly system, but there are still examples that show how a monopoly can negate supply and demand principles. For example, movie houses typically do not allow patrons to bring outside food and beverages into the theater. This gives that business a temporary monopoly on food services, which is why popcorn and other concessions are so much more expensive than they would be outside of the theater. Traditional supply and demand theories rely on a competitive business environment, trusting the market to correct itself.

Planned economies, in contrast, use central planning by governments instead of consumer behavior to create demand. In a sense, then, planned economies represent an exception to the law of demand in that consumer desire for goods and services may be irrelevant to actual production.

Price controls can also distort the effect of supply and demand on a market. Governments sometimes set a maximum or a minimum price for a product or service, and this results in either the supply or the demand being artificially inflated or deflated. This was evident in the 1970s when the U.S. temporarily capped the price of gasoline at about $1 per gallon. Demand increased because the price was artificially low, making it more difficult for the supply to keep pace. This resulted in much longer wait times and people making side deals with stations to get gas.

While we've mainly been discussing consumer goods, the law of supply and demand affects more abstract things as well, including a nation's monetary policy. This happens through the adjustment of interest rates. Interest rates are the cost of money: They are the preferred tool for central banks to expand or decrease the money supply.

When interest rates are lower, more people are borrowing money. This expands the money supply; there is more money circulating in the economy, which translates to more hiring, increased economic activity, and spending, and a tailwind for asset prices. Raising interest rates leads people to take their money out of the economy to put in the bank, taking advantage of an increase in the risk-free rate of return; it also often discourages borrowing and activities or purchases that require financing. This tends to decrease economic activity and put a damper on asset prices.

In the United States, the Federal Reserve increases the money supply when it wants to stimulate the economy, prevent deflation, boost asset prices, and increase employment. When it wants to reduce inflationary pressures, it raises interest rates and decreases the money supply. Basically, when it anticipates a recession, it begins to lower interest rates, and it raises rates when the economy is overheating.

The law of supply and demand is also reflected in how changes in the money supply affect asset prices. Cutting interest rates increases the money supply. However, the amount of assets in the economy remains the same but demand for these assets increases, driving up prices. More dollars are chasing a fixed amount of assets. Decreasing the money supply works in the same way. Assets remain fixed, but the number of dollars in circulation decreases, putting downward pressure on prices, as fewer dollars are chasing these assets.

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How Does the Law of Supply and Demand Affect Prices?

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The law of supply and demand is an economic theory that explains how supply and demand are related to each other and how that relationship affects the price of goods and services. It's a fundamental economic principle that when supply exceeds demand for a good or service, prices fall.

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In this article, it exemplifies how economic advisers assured their bosses that recovery would be rapid. There was been numerous instances where downfalls in prosperity resulted in financial losses. People want to be prepared and packed with supplies, medications, or equipment in case any natural or physical disasters occur. During holidays, sales are rapidly promoted so people can prepare what supplies are liable.
I predict prices will change in the real world market because everyone wants to conserve their purchases in hopes of diminishing debt or not wasting time. If they know beforehand the prices that are at its best value, they'll more likely buy it at their own benefit.

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The World Economic Forum is an independent international organization committed to improving the state of the world by engaging business, political, academic and other leaders of society to shape global, regional and industry agendas. Incorporated as a not-for-profit foundation in 1971, and headquartered in Geneva, Switzerland, the Forum is tied to no political, partisan or national interests.

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In this article, it exemplifies how a popular celebrity or athlete can endorse a product more efficiently. Its an important factor in promotions because people have different desires. If a large majority moralizes a brand, chances are higher of more costumer satisfaction. Companies engage in this type of advertising because an audience, we view the product as more enhanced.
I predict prices will change in the real world market because companies are aware and alert of the trends that teenagers, especially, gravitate for. If they know people are going to purchase it anyway, prices will go up because everyone is collectively interested n it.

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This post was updated in August 2018 to include new information and examples.

This post asks the question of what happens in the market for a good or service when the tastes or preferences for the good or service change. This question fits into our discussion about the determinants of demand.

One of the determinants of demand is the current state of tastes and preferences for the good or service. In this example, we will be focusing on the services for Romanian translation. This may seem like an obscure topic, and it is to most people which will limit our demand for the service. Because of our tastes or preferences for this specific service, we will have a low demand for it, especially compared to the demand for Spanish or Chinese translation services. But imagine if the U.S. or Europe signed a new free trade agreement, or began spending billions of dollars in business opportunities in Romania. This would potentially change our tastes and preferences for this service, and likely shift the demand curve right/up.

Remember that tastes and preferences for a good or service are held constant when we construct the demand curve, the only things that we are allowing to change are the price and the quantity (for more info look at the discussion on endogenous vs exogenous variables). Because of this, when some event occurs, like increased business opportunities in Romania, we will see a change in preferences to conduct business with Romanian translation companies. In our example, it is a positive change in preferences (more business opportunities) so we will see the demand curve shift right/up or increase, which is shown in the graph below:

You can see that when we increase demand (shift the demand curve right/up) it results in an increase of both equilibrium price AND quantity. This is easily visible by looking at the red dots marked 1 and 2. Initially we were at equilibrium point 1 in the market for Romanian translation services, but after the news of increased business opportunities we move to equilibrium point 2. This means that prices for these services have gone up, as well as the total quantity of these services that are now used.

Here are some other examples you can consider when looking at how a change in tastes and preferences affect the demand curve and equilibrium price and quantity.

1) A popular athlete or celebrity endorses a product:

Imagine someone really popular (perhaps Tom Brady, or Cristiano Ronaldo) endorses a new type of deodorant. We all objectively know that a celebrity endorsement has no affect on the effectiveness of a good or service but we can't help but think we will be a little more popular or perhaps their may be some other hidden quality about the product that we are not aware of. This helps boost demand for a product--which is why companies engage in this type of advertising.

2) We discover a product is healthier than we originally thought:

Funny but true example, Kale was never a popular food choice in America until after 2000. Before then its most common purpose was to act as a border for food at buffets! Now Kale is extremely popular as a food choice and we have seen prices and consumption rise significantly. This is a classic example of tastes and preferences affecting demand for a product (we learn something is healthy or good for us).

There are two big ideas to take away from this lesson about tastes and preferences and how they affect the demand curve:

1) A positive change in tastes or preferences increases demand (shifts it right/up). A negative change in tastes and preferences will decrease demand (shift it left/down).

2) If tastes and preferences improve and supply stays that same, then both price and quantity go up. If tastes and preferences sour (make demand decrease) then we would expect market price and market quantity to decrease.

Also, the video below goes through examples and the creation of multiple graphs if you need help developing your intuitive understanding of how tastes and preferences can affect the demand curve and the resulting market price and market quantity.

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How a change in tastes and preferences affects market price and market quantity

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This post was updated in August 2018 to include new information and examples. This post asks the question of what happens in the market for a good or service when the tastes or preferences for the good or service change. This question fits into our discussion about the determinants of demand.

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In this article, it exemplifies how every person is a consumer. We're the catalyst for companies to profit and flourish as an economy. For example, in California, natural disasters are obligated to occur. Therefore, insurance, real estates,  and health care is heavily needed among many citizens. The more people there are, the more interest received.
I predict prices will change in the real world market because if more people are keen on purchasing a certain product, companies can take advantage for their benefit by raising prices. More people = more money for companies

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Consumer spending is what households buy to fulfill everyday needs. This private consumption includes both goods and services. Every one of us is a consumer. The things we buy every day create the demand that keeps companies profitable and hiring new workers.

Almost two-thirds of consumer spending is on services, like real estate and health care. Other services include financial services, such as banking, investments, and insurance. Cable and internet services also count, and even services from non-profits.

The remaining one-third of our personal consumption expenditure is on goods. These include so-called durable goods, such as washing machines, automobiles, and furniture. More frequently, we buy non-durable goods, such as gasoline, groceries, and clothing.

Five Determinants of Consumer Spending

There are five determinants of consumer spending. These are the things that affect how much you spend. Changes in any of these components will affect consumer spending.

The most important determinant is disposable income. That's the average income minus taxes. Without it, no one would have the funds to buy the things they need. That makes disposable income one of the most important determinants of demand. As income increases so does demand. If manufacturers ramp up to meet demand, they create jobs. Workers' wages rise, creating more spending. It's a virtuous cycle leading to ongoing economic expansion. If demand increases but manufacturers don't increase supply, then they will raise prices. That creates inflation.

The second component is income per capita. It tells you how much each person has to spend. Income measurements might rise just because the population increases. Income per person reveals whether each person's standard of living is also improving.

Income inequality is the third determinant of spending. Some people's income may rise at a faster pace than others. The economy benefits when most of the gain goes toward low-income families. They must spend a more significant share of each dollar on necessities until they reach a living wage. The economy doesn't benefit as much when increases go toward high-income earners. They are more likely to save or invest additions to income instead of spending.

The fourth factor is the level of household debt. That includes credit card debt, auto loans, and school loans. Current consumer debt statistics show that household debt has reached new record levels. Surprisingly, high health care costs are one of the biggest causes of overwhelming debt.

The fifth determinant is consumer expectations. If people are confident, they are more likely to spend now. The Consumer Confidence Index measures how confident people are about the future. It includes their expectations of inflation. If consumers expect inflation to be high, they will buy more now to avoid future price increases. That's why the Federal Reserve targets a 2% inflation rate.

How It Affects You

Consumer spending is the single most important driving force of the U.S. economy. Keynesian economic theory says that the government should stimulate spending to end a recession. On the other hand, supply-side economists believe the government should cut business taxes to create jobs. But companies won't boost production without demand no matter how low taxes are.

If you doubt this, think about what would happen if everyone stopped spending. Businesses would eventually go bankrupt and lay off workers. The government would then have no one to tax.

The economy would have to rely on exports, assuming other countries kept up their consumer spending. Borrowing would keep the government and factories open. These additional components of the gross domestic product aren't as critical as consumer spending.

Even a small downturn in consumer spending damages the economy. As it drops off, economic growth slows. Prices drop, creating deflation. If slow consumer spending continues, the economy contracts.

But too much of a good thing can also be damaging. When consumer demand exceeds manufacturers' ability to provide the goods and services, prices increase. If this goes on, it creates inflation. If consumers expect ever-increasing prices, they will spend more now. That further increases demand, forcing businesses to raise prices. It becomes a self-fulfilling prophecy that 's hard to stop. That's why the primary mandate of the nation's central bank, the Federal Reserve, is to ward off inflation.

How Consumer Spending Is Measured

Consumer spending is measured in many different ways. The most comprehensive is the monthly Personal Consumption Expenditures (PCE) report.

The Consumer Expenditure Survey is released in August each year by the Bureau of Labor Statistics. It is similar to the PCE but has a little more detail about types of households. That's because the BLS analyzes data from the U.S. Census. The BLS releases the most current report in September each year.

Retail sales is another component of consumer spending. You can check how healthy it is with the most recent retail sales statistics.

The Bottom Line

Consumer spending drives a significantly large part of U.S. GDP. This makes it one of the biggest determinants of economic health. Data on what consumers buy, don't buy, or wish to spend their money on can tell you a lot where the economy may be heading. Watching the trend on consumer spending can serve as an invaluable tool for managing your investments.

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What You Buy Every Day Drives U.S. Economic Growth

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Consumer spending is what households buy to fulfill everyday needs. This private consumption includes both goods and services. Every one of us is a consumer. The things we buy every day create the demand that keeps companies profitable and hiring new workers. Almost two-thirds of consumer spending is on services, like real estate and health care.

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In this article, it exemplifies how less developed, distinguished countries equal lower demands for food consumption because money is desperately needed. Jobs result and vary with financial stability so if an individual receives a promotion, chances are, they'll purchase more food. If money is scarce, food may not be the first priority so demands will decrease.
I predict prices will change in the real world market because if income is low, products will be more inexpensive. Demands wouldn't be anticipated or acquired simply because an individual's ability and willingness isn't achievable.

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This section tries to illustrate with a simple example, the size of potential changes in food demand arising from different income distribution scenarios. We perform two simple simulations of the effect of changes in income distribution on food demand within a country and between countries in the world. The simulation is performed using Engel curves estimated by semi-logarithmic functions and by assuming a lognormal distribution of income within countries and in the world. These assumptions are oversimplifying the complex relationship between income distribution and food demand, and other types of simulation are possible. The purpose of the exercise is to provide an initial rough approximation to the size of these effects both within and between countries.

(a) Within-country inequality and food demand

In order to provide an example of the effect of changes in income distribution on food demand within an economy, we perform a simulation using data from a sample of households in Andhra Pradesh (India) conducted in 2005 by the NSSO (2006). We estimate the food Engel curve using the semilogarithmic and the food share forms. The fitted values are shown in . The estimate income elasticity is very high (0.72).

A simple simulation can be performed assuming that the distribution of income is lognormal and exploiting the following property of the lognormal distribution ( Prais & Houthakker 1971). The arithmetic mean ( ) of the lognormal distribution is related to the geometric mean ( y*) by the following relationship: , where σ y ² is the variance in the distribution of the logarithm of income. Substituting this expression for the mean of logarithm income in equation (2.3), this can be re-written as:

The average food consumption is now a function of both average income and of the variance of income. Mean preserving changes in inequality can be simulated by changing the values of the variance of income. In order to represent the changes in the income distribution with an index, which is more familiar to the readers, and for which data are readily available, we use another property of the lognormal distribution. If the distribution of income is lognormal, the Gini coefficient can be derived from the variance of the lognormal distribution in the following way ( Cowell 2008):

The initial value of the Gini coefficient is relatively low (0.28). We simulated changes in the Gini of two decimal points above and below the initial value and calculated the corresponding food consumption. The results are displayed in .

The elasticity of food consumption to the Gini coefficient estimated from this curve is approximately −0.2, indicating that an increase by 10 per cent in the Gini, a change not far from those normally observed within one or a few years, would reduce per capita food consumption by about 2 per cent.

This simulation is valid under the assumption that the shape of the Engel curve does not vary over time, which is equivalent to assuming that changes in income levels over time for the same household are mirroring income changes across different households at a single point in time. In other words, food consumption of households with different income levels is used to predict food consumption by the same household when its income increases. Another way to express this is that the shape of the Engel curve should not vary over time. There are a number of reasons, however, that suggest that the shape of the curve might vary over time. Firstly, households may stick to their diets for some time after income changes rather than quickly adopting the diets of richer households. In this case, the change in food consumption over time would be smaller than the change in consumption over the cross section of households, and the Engel curve would be steeper. Secondly, consumer preferences, which determine consumption with income and prices, may change, and as a result alter the shape of the Engel curve. One obvious case is the change in family composition or size over time, because people of different age have different consumption needs. Children in particular tend to consume proportionally more food than adults in developing countries. In this case, the change in food consumption over time, following, for example, a decrease in average family size, would be larger than the change in consumption over the cross section of households, and the Engel curve would be flatter. Finally, new goods can be introduced over time and food luxury items may appear on the market, which attract new consumers. The introduction of these items might shift upwards the right section of the Engel curve putting into question the existence of a 'saturation' point. All these possible effects suggest that the invariance of the shape of the Engel curve over time should be tested with the survey data rather than assumed. If Engel curves can be estimated from several cross-sectional surveys that are years apart from each other, then parametric and non-parametric tests are available to assess the stability of the curves over time.

We also simulated the pattern of per capita food consumption over the next 40 years. To do so we assumed a rate of per capita income growth of 4.1 per cent per year. As per capita income increases over time, per capita food consumption moves along the food Engel curve. However, if the incomes of the poor and the rich grow at different rates and the distribution of income varies, then the patters of food consumption deviate from the Engel curve. We estimated a very large change in the Gini coefficient by ±20 per cent over a 40 year period, and calculated the levels of per capita food consumption for each year.

The results of these simulations are shown in . A more egalitarian distribution has the effect of increasing per capita food consumption, while a less egalitarian distribution produces the opposite outcome. The chart on the left of shows the deviations from the Engel curve, while the chart on the right shows the levels of per capita food consumption over time. Under the assumptions made in the simulation, an increase in inequality by 20 per cent over 40 years will produce a reduction in per capita food demand by about 2 per cent. Conversely, a reduction in the Gini coefficient by 20 per cent would result in 40 years in an increase in per capita food consumption by about 1.6 per cent. Clearly, the impact of changes of income distribution, even when considering very large changes, on per capita food demand in this case is small, since inequality in Andhra Pradesh is not high.

Regarding food composition, the effects of changes in income distribution on specific food items depend on the shape of the Engel curve for that particular item. displays Engel curves in share form for six broad food categories (cereals, pulses, dairy, fats, meat, and fruit and vegetable) for the sample of household in Andhra Pradesh. Expenditure is expressed as a share of total expenditure. In this way, a concave down Engel curve implies a falling share, while a concave up form implies an increasing share. The curves were calculated employing semi-parametric methods in order to let the data define the shape of the curve rather than imposing any specific functional form ( Yatchew 2003).

The Engel curve for cereals has a concave down shape for most of the expenditure range, but is concave up for very poor households. Only the Engel curves for dairy and meat show a clear pattern. Dairy is consumed more than proportionally as expenditure increases, while the share of expenditure in meat consistently decreases as expenditure increases. Changes in income distribution for these food items are clearly predictable. An increase in inequality increases the consumption of dairy products and reduces the consumption of meat. The effects of changes in income distribution on the consumption of other food items are much less predictable because the Engel curves in share form have an inverted U shape. Whether consumption increases or decreases depends on the nature of the transfer taking place. For example, while as a general rule an increase in inequality reduces consumption of cereals, if the increase in inequality is circumscribed among the very poor (the rising section of the cereals Engel curve in ), cereals consumption increases.

(b) Between-country inequality and food demand

Since data are available on food consumption and per capita gross domestic product (GDP) for most countries of the world, it is tempting to proceed to the estimation of a world food Engel curve and to perform a world-scale simulation of a change in the world income distribution. shows the estimation of semilogarithmic and share form food Engel curves for most countries in the world using the data of the International Comparison Programme of the World Bank. Circles represent countries, and their size is proportional to the population of each country. The large circle of the United States on the right, and of India and China on the left, are clearly visible. The world income elasticity of food consumption estimated by these curves is 0.48.

The simulation of the effect of changes in the world income distribution on world food demand can be performed in the same way as within a single country. However, before carrying out the simulations, the concept of world income inequality needs to be properly defined. There are three main concepts of income inequality in the world ( Milanovic 2005). The first concept, international inequality, is inequality between states, where each country is represented by one single observation. This concept is clearly inappropriate for the present analysis because it is not representative of consumption behaviour in the world. The second concept, global inequality, is inequality among world citizens as could be obtained by running a random income survey over the entire world. This concept represents the true income inequality in the world but data for its calculation are not readily available. The third concept, between-country inequality, is inequality between countries, where each country is represented by the number of its citizens. In other words, this concept measures inequality among individuals, but each individual is assigned the average income of her country of residence. This is the concept used in estimating the charts of . Between-country inequality ignores within-country inequality and, as any form of income averaging by aggregation, it underestimates the true global world inequality. It is estimated, however, that between-country inequality captures around 80 per cent of global inequality ( Anand & Segal 2008), and it represents therefore a good approximation of global inequality. In our data, the estimated world Gini coefficient is 0.56, which compares relatively well to estimates of 0.7 often found for global income inequality.

The world income distribution is assumed to be normal in the logarithms as it was the case of the within-country distribution. There is not strong support in the data for this particular parametric form as the true distribution of income, including within-country inequality, is not known, but it is an approximation often used by studies investigating world inequality (e.g. Chotikapanich et al. 1997; Dowrick & Akmal 2005).

shows the relationship between the world average food consumption and the world Gini coefficient. The elasticity of food consumption to the Gini coefficient estimated from this curve is −1, indicating that a reduction by 1 per cent in the world Gini would increase per capita food consumption by the same percentage amount. This elasticity is much larger than the one observed within-country, presumably a consequence of the different curvature of the world Engel curve and of the world income distribution compared with the national ones. Year-to-year estimates of world Gini are not easily available because of difficulties in obtaining the required data. Sala-i-Martin (2006), for example, estimated a reduction in global income inequality by 0.8 per cent over 1992 and 1993. According to our estimates, a 0.8 per cent increase in per capita global food demand should have occurred over the same years only on account of a change in the world distribution of income.

We also repeated the simulation performed for Andhra Pradesh for the whole world, assuming a per capita income growth of 2.6 per cent per year. We predicted trends in the world distribution of income using historical series of the Gini coefficient calculated by Sala-i-Martin (2006) and by Milanovic (2009). The trends are extrapolations over time of the Gini of global income distribution calculated from an 'optimistic' point of view (Sala-I-Martin) and a 'pessimistic' point of view (Milanovic), respectively. Theoretically, the two views are supported by diverging hypotheses regarding convergence or divergence of world economies. The results are shown in . The effect of changes in the income distribution is considerable. Under the assumptions made, an increase in Gini inequality by 8 per cent over 40 years will produce a reduction in per capita food demand by about 5.4 per cent, while a reduction in the Gini coefficient by 5 per cent would result in 40 years in an increase in per capita food consumption by about 2.7 per cent compared with the income distribution-neutral growth case. These effects, however, are not large if compared with the effects of increases in per capita income. For example, the increase in consumption of food following per capita income growth alone, independently of changes in income distribution, over the same period of 40 years is nearly 50 per cent. Given the estimated expenditure elasticity of world food consumption (0.47), the increase in food consumption obtained under the most optimistic prediction of a 5 per cent fall in the Gini over 40 years might be obtained in just slightly over 2 years of per capita income growth at the current levels.

The much larger effect of income distribution on food demand between countries than within countries is explained by the wider differences in demand elasticities between countries in the world compared with the differences between individuals within countries. This illustration underlines the point that shifts in food demand deriving from changes in the income distribution are to be expected to originate from the patterns of convergence or divergence between world economies rather than from the trends in inequality within each country. However, it should also be emphasized that predictions of future world income distribution were obtained by extrapolating calculated series of Gini coefficients. Without some strong theoretical assumptions regarding convergence or divergence of world economies, it is difficult to interpret these extrapolations as 'trends'. These predictions are, to some extent, only hypothetical: the increasing inequality trend might be reversed and vice versa.

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Income distribution trends and future food demand

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This section tries to illustrate with a simple example, the size of potential changes in food demand arising from different income distribution scenarios. We perform two simple simulations of the effect of changes in income distribution on food demand within a country and between countries in the world.