The Uncertain Unit Root in the U.S. Poverty Rate

1998 ◽  
pp. 89-104
Author(s):  
Baldev Raj ◽  
Daniel J. Slottje
Keyword(s):  
Unit Root ◽  
Poverty Rate ◽  
The U.S

The uncertain unit root in the U.S. poverty rate

1997 ◽  
Vol 22 (4) ◽  
pp. 555-570 ◽  
Author(s):  
Baldev Raj ◽  
Daniel J. Slottje
Keyword(s):  
Unit Root ◽  
Poverty Rate ◽  
The U.S

scholarly journals Convergence Of Market Shares In The U.S. Cigarette Industry

2011 ◽  
Vol 19 (4) ◽  
Author(s):  
Craig A. Gallet
Keyword(s):  
Market Share ◽  
Unit Root ◽  
Short Paper ◽  
Cigarette Industry ◽  
Long Run ◽  
Market Shares ◽  
The U.S

Many studies examine the degree of rivalry in an industry by utilizing measures of market share instability, with greater (lesser) volatility of market shares coinciding with greater (lesser) rivalry. This short paper extends this line of research by addressing long run instability of market shares. In particular, we test for the convergence of market shares in the U.S. cigarette industry using unit root procedures. Our finding that market shares for pairs of firms rarely converge suggests that market shares are unstable in the long run. Hence, rivalry has remained quite intact in the cigarette industry.

scholarly journals MEASURING POVERTY CYCLES IN THE U.S. 1959–2013

2018 ◽  
Vol 24 (4) ◽  
pp. 1737-1754 ◽  
Author(s):  
Marinko Škare ◽  
Romina Pržiklas Družeta ◽  
Damian Škare
Keyword(s):  
Business Cycles ◽  
Time Series Data ◽  
Well Being ◽  
Poverty Rate ◽  
Series Data ◽  
Poverty Dynamics ◽  
The Usa ◽  
Shed Light ◽  
The U.S ◽  
Economic Well Being

This paper aims to shed light on the nature of poverty as a dynamic process by examining poverty cycles, their magnitudes, and their asymmetry. The designated benchmark country is the USA due to the availability of time series data making comprehensive analyses possible. We use Harding and Pagan (2002) and the Cardinale and Taylor (2009) model to isolate poverty cycles in the U.S. during 1959–2013. Once isolated, we test the poverty cycles for duration dependency, and their synchronization with the U.S. business cycles observed over the same period. We find that poverty dynamics measured through poverty cycles differ for alternative poverty rate indicators. Another critical point is the magnitude of change in the poverty cycles. Prolonged and more volatile poverty cycles have a significant adverse impact on people and families facing them. That is particularly important for policymakers who should rethink poverty policy guidelines aimed at helping people with more volatile poverty cycles first. Our is the first study, to our knowledge, to isolate poverty cycles and focus on their nature. Poverty cycles should attract more attention from policymakers since they more accurately assess nations’ economic well-being than output (GDP).

TESTING FOR A UNIT ROOT IN LEE–CARTER MORTALITY MODEL

2017 ◽  
Vol 47 (3) ◽  
pp. 715-735 ◽  
Author(s):  
Xuan Leng ◽  
Liang Peng
Keyword(s):  
Unit Root ◽  
Finite Sample ◽  
Asymptotic Results ◽  
Inference Procedure ◽  
Mortality Model ◽  
Mortality Index ◽  
R Packages ◽  
Mortality Projections ◽  
The U.S ◽  
Carter Model

AbstractMotivated by a recent discovery that the two-step inference for the Lee–Carter mortality model may be inconsistent when the mortality index does not follow from a nearly integrated AR(1) process, we propose a test for a unit root in a Lee–Carter model with an AR(p) process for the mortality index. Although testing for a unit root has been studied extensively in econometrics, the method and asymptotic results developed in this paper are unconventional. Unlike a blind application of existing R packages for implementing the two-step inference procedure in Lee and Carter (1992) to the U.S. mortality rate data, the proposed test rejects the null hypothesis that the mortality index follows from a unit root AR(1) process, which calls for serious attention on using the future mortality projections based on the Lee–Carter model in policy making, pricing annuities and hedging longevity risk. A simulation study is conducted to examine the finite sample behavior of the proposed test too.

scholarly journals The Effect of Benefit Underreporting on Estimates of Poverty in the United States

2019 ◽  
Author(s):  
Zachary Parolin
Keyword(s):  
United States ◽  
Household Income ◽  
The United States ◽  
Poverty Rate ◽  
Median Income ◽  
Poverty Measure ◽  
Income Transfers ◽  
Households With Children ◽  
Percent Decline ◽  
The U.S

The household income data used most frequently to estimate poverty rates in the United States substantially underreports the value of means-tested transfers. This paper investigates how underreporting affects estimates of the incidence and composition of poverty in the U.S. from 2013 to 2015. Specifically, I apply benefit adjustments for the underreporting of three social transfers to the Current Population Survey (CPS ASEC) to provide more accurate estimates of poverty rates. Diagnostic checks indicate that the imputed benefit adjustments are imperfect, but do provide a more accurate representation of household income than the uncorrected CPS ASEC data. In 2015, the benefit adjustments add more than $30 billion of income transfers to the CPS ASEC, primarily concentrated among low-income households with children. I test the effects of the benefit corrections on two conceptualizations of poverty: the U.S. Supplemental Poverty Measure (SPM) and a relative measure of poverty set at 50 percent of federal median income. In 2015, the SPM poverty rate for the total population falls from 14.3 to 12.7 percent, a 1.6 percentage point (11 percent) decline, after adjusting for underreporting. Among children, the SPM poverty rate falls from 16.1 to 12.8 percent, a 3.3 percentage point (20 percent) decline. The percent-of-median poverty rate experiences similar declines after applying the benefit imputations. The findings suggest that the unadjusted CPS ASEC data meaningfully overestimates the incidence of poverty in the U.S., particularly among households with children. Documentation for applying the benefit corrections to the CPS ASEC is provided for improved estimates in future poverty research.

scholarly journals Examining the Linkage between Poverty and Macroeconomic Variables in Malaysia: A Co-integration Analysis

2017 ◽  
Vol 9 (2) ◽  
pp. 6-15
Author(s):  
Gurmit Kaur ◽  
Siti Ayu Jalil
Keyword(s):  
Unit Root ◽  
Consumer Price Index ◽  
Percent Level ◽  
Unit Root Test ◽  
Wald Test ◽  
Poverty Rate ◽  
Causality Test ◽  
Macroeconomic Variables ◽  
Integration Test ◽  
Integration Analysis

The purpose of this paper is to examine the linkage between the macroeconomic variables i.e. gross domestic product per capita (GDP), unemployment (UNE), tourist receipts (TOU), consumer price index (CPI) and poverty rate (POV) in Malaysia from 1969-2014. The econometric techniques used are unit root test and the Johansen Cointegration. The Granger Causality test using Block Exogeneity Wald test was added to analyze the causal relationships between the variables. The unit root test showed that all variables were stationary at first difference and thus the Johansen Co-integration test is an appropriate technique to employ. The evidence from co-integration test indicates that all the five series have three (3) co-integrating equations and significance at 1 percent level of significance. The causality test indicated there is a significant unidirectional causality between POV on GDP, CPI on POV, POV on TOU, GDP on UNE, GDP on TOU and CPI on TOU and bidirectional causality between POV and UNE. This paper is possibly the first to discuss these relationships in Malaysian context using Co-integration analysis. The finding implies that poverty is the key issue that should be addressed to achieve a high-income country status in the year 2020.

Unit Root Tests, Persistence, and the Unemployment Rate of the U.S. States

2007 ◽  
Vol 73 (3) ◽  
pp. 698-716
Author(s):  
Diego Romero‐Ávila ◽  
Carlos Usabiaga
Keyword(s):  
Unemployment Rate ◽  
Unit Root ◽  
Unit Root Tests ◽  
The U.S

scholarly journals ANALISIS KELAYAKAN DOLAR AMERIKA, EURO, DAN DINAR EMAS DALAM KONVERSI DOLAR AMERIKA SEBAGAI ALAT LINDUNG NILAI DENGAN EMAS SEBAGAI ALAT UKUR DALAM LAPORAN KEUANGAN

MAKSIMUM ◽  
2016 ◽  
Vol 3 (1) ◽  
pp. 18
Author(s):  
Praditya Dewi Arumsari ◽  
Ayu Noviani Hanum
Keyword(s):  
Time Series ◽  
Financial Reporting ◽  
Unit Root ◽  
Accounting Information ◽  
Secondary Data ◽  
Monthly Data ◽  
Steady Rate ◽  
Exchange Rate Movements ◽  
The Stability ◽  
The U.S

For this study was to analyze the potential of the Gold Dinar as a hedging tool replaces the U.S. Dollar. U.S. Dollar in recent year experienced extreme exchange rate movements so that researchers analyzed the stability of the current compared to Euro that threatening position U.S. Dollar as the worlds major currencies. Stable currency has the accuracy and reliability in an accounting information to make decisions of an organization or company. The data used in this study is secondary data by type of time series. Monthly data from 2003 antil 2012. To determine the stability of each currency, the data obtained should be free from containt of the unit root, has a normal distributed, and constant. The volatility calculation of 0.0408792 (Gold Dinar), 0.0408790 (U.S. Dollar), and 0.040540 (Euro). Volatility is a statiscal measure of the diversion returns for a given security. From the research that has been done, calculation of the Euro states have a low risk of change in value and have a steady rate. With that result, Euro can be reference currency in financial reporting.Keywords: Hedging, U.S. Dollar, Euro, Gold Dinar, Gold, Accounting Information, Financial Reporting.

scholarly journals Concentrated Poverty

2011 ◽  
pp. 1-6
Author(s):  
Dionissi Aliprantis ◽  
Mary Zenker
Keyword(s):  
United States ◽  
Geographic Distribution ◽  
The United States ◽  
Poverty Rate ◽  
Concentrated Poverty ◽  
The Poor ◽  
The U.S

Although the U.S. poverty rate was the same in 2000 as it was in 1970, the geographic distribution of the poor has become more concentrated. A higher concentration of poor in poor neighborhoods is a concern because it may mean the poor are exposed to fewer opportunities that affect their outcomes in life, like employment and income. We show where and how poverty has become more concentrated in the United States, and who is most likely to be affected.

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