A Critical Statistic
You can think of the amount you spend on goods and services (from essentials for you and your dependents, to wants and desires), and the income you actually are making as a ratio: Spending/Income. I hypothesize that by reducing this ratio for as many individuals in society as possible, you're more able to meet your society's demand potential, have your economy grow and develop, and be more resilient if people choose to save the excess.
Spending can be calculated using a similar methodology to the University of Washington's "Self-Sufficiency Standard" to determine the costs of living for a given geographic area. It can also be based on actual spending in the economy beyond the bare minimum needed to provide for oneself and one's dependents. Income data can be obtained through the US Census Bureau for that geographic area. Both sides of this statistic can be affected by public policy and market forces. Either prices change in the market, or the costs of government get shifted among the different income groups. These are the primary ways to alter the ratio to have society be better or worse off. Both sides can be influenced by public policy directly (ie, through different tax structures), or indirectly (ie, through publicly funded research to lower the costs of production and distribution).
Lower income people are more sensitive to changes in spending and income than people with higher incomes. Likewise, the higher percentage of people you're able to actually minimize the ratio for, the more likely it is that your economy will do well. Ratios above 1 are when people are spending more than they are making, while ratios of 0 indicate no spending is needed. It is unlikely that the ratio would dip below 0, because to do so would imply that everything a person needs comes at zero cost in the market. Each geographic area likely has a baseline cost of living for different family configurations (which is what the University of Washington's "Self-Sufficiency Standard" explicitly looks at). A measurable goal in poverty reduction (excluding the social, psychological, and physical effects of poverty reduction) would be to minimize this ratio through public policy and interventions in the market by reducing the cost of living in the society, or by increasing peoples' incomes through different compensation laws and tax regimen.
It should be noted that the spending-to-income ratio does not account for the environmental impacts of peoples' or organizations' economic activities. Environmental impacts arguably have a greater impact on a society's chances of survival and ability to prosper than this ratio. The spending-to-income ratio is merely a means to see how much people either need to or are spending relative to their incomes. Even though this is the only thing that this statistic does, it likely can infer a lot about the economic health of a given society and peoples' abilities to achieve standards of living for themselves and their dependents. More research would have to be done in order to confirm or reject the null hypothesis that this statistic does not affect outcomes in the society and economy. Forward-lagged regression analyses with different economic and social indicators as dependent variables could be a method for understanding if this hypothesis is accurate.
Spending can be calculated using a similar methodology to the University of Washington's "Self-Sufficiency Standard" to determine the costs of living for a given geographic area. It can also be based on actual spending in the economy beyond the bare minimum needed to provide for oneself and one's dependents. Income data can be obtained through the US Census Bureau for that geographic area. Both sides of this statistic can be affected by public policy and market forces. Either prices change in the market, or the costs of government get shifted among the different income groups. These are the primary ways to alter the ratio to have society be better or worse off. Both sides can be influenced by public policy directly (ie, through different tax structures), or indirectly (ie, through publicly funded research to lower the costs of production and distribution).
Lower income people are more sensitive to changes in spending and income than people with higher incomes. Likewise, the higher percentage of people you're able to actually minimize the ratio for, the more likely it is that your economy will do well. Ratios above 1 are when people are spending more than they are making, while ratios of 0 indicate no spending is needed. It is unlikely that the ratio would dip below 0, because to do so would imply that everything a person needs comes at zero cost in the market. Each geographic area likely has a baseline cost of living for different family configurations (which is what the University of Washington's "Self-Sufficiency Standard" explicitly looks at). A measurable goal in poverty reduction (excluding the social, psychological, and physical effects of poverty reduction) would be to minimize this ratio through public policy and interventions in the market by reducing the cost of living in the society, or by increasing peoples' incomes through different compensation laws and tax regimen.
It should be noted that the spending-to-income ratio does not account for the environmental impacts of peoples' or organizations' economic activities. Environmental impacts arguably have a greater impact on a society's chances of survival and ability to prosper than this ratio. The spending-to-income ratio is merely a means to see how much people either need to or are spending relative to their incomes. Even though this is the only thing that this statistic does, it likely can infer a lot about the economic health of a given society and peoples' abilities to achieve standards of living for themselves and their dependents. More research would have to be done in order to confirm or reject the null hypothesis that this statistic does not affect outcomes in the society and economy. Forward-lagged regression analyses with different economic and social indicators as dependent variables could be a method for understanding if this hypothesis is accurate.
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