Huawei could team up with one of these relatively fringe mobile players to sell Mate phones with one of these Wi-Fi plus cellular phone plans.  There's no better time to try than now. 

. Maybe Amazon can also -- as it does with its own Kindle devices and some Android smartphones -- lower Mate prices by offering the phones with Amazon-sold advertisements on the home screens. 

the model simulations indicate thatdierent dimensions of nancial inclusion have a dierential impact on GDP and inequality and thatthere are trade-os. There also exist rich interactions among the dierent dimensions of nancialinclusion. Financial sector policies that address these dimensions could be complementary in naturewith each other, but it can also be the case that implementing one policy reduces the eectivenessof other policies.

In this section, we zoom-in on a numerical comparison of the marginalresponses of income and inequality. The numbers in Table 3 are calculated as dierences betweenthe current state of the country (shown with the circle in 3-8) and the eventual steady-state valuewhen the economy's credit to investment ratio is increased by one percentage point.

e distance to a bank branch matters for credit access, which suggeststhat policies that promote branch openings in rural, unbanked locations would help reduce the creditparticipation cost

Impact on GDP and Inequality: A Numerical Comparison

Table 1: Overview of the Data

We calibrate the model for 6 countries at various stages of economic development: 3 low-incomecountries (Uganda in 2005, Kenya in 2006, and Mozambique in 2006), and 3 emerging marketeconomies (Malaysia in 2007, Philippines in 2008 and Egypt in 2007).

, the policy that is most eectivein increasing access (reducing participation costs) benets the poor and talented agents primarily,while wealthy agents lose due to higher interest rates and wages. By contrast, policies that targetnancial depth (relaxing borrowing constraints) benet wealthy and talented agents but can imposelosses on wealthy but less-talented agents.

The model simulations also indicate that dierent dimensions of nancial inclusion unambiguouslyincrease the economy's TFP as talented entrepreneurs, who desire to operate rms at a larger scale,benet disproportionately. However, they have a dierential impact on GDP and inequality andthere are trade-os.

The quantitative model developed in this paper enables us to examine the impact of variousnancial inclusion policies on GDP, income inequality (measured by the Gini coecient) and overallwelfare

We calibrate the model using data from the World Bank Enterprise Surveys and World Devel-opment Indicators

The Enterprise Survey is a rm-level survey of a representative sample of rmsin an economy.

Once in the credit regime, individuals can obtain credit, but its size is constrained by twoadditional types of nancial frictions { limited commitment and asymmetric information. Thesedistort the allocation of capital and entrepreneurial talent in the economy, lowering aggregatetotal factor productivity (TFP). T

The model features an economy with two \nancial regimes", one with credit and one withsavings only. Individuals in the savings regime can save (i.e., make a deposit in nancial institutionsto transfer wealth over time) but cannot borrow. Participation in the savings regime is free, butindividuals must may a participation cost to borrow.

In the model, agents are heterogeneous { distinguished from each other by wealth and talent.Individuals choose in each period whether to become an entrepreneur or to supply labor for a wage.Workers supply labor to entrepreneurs and are paid the equilibrium wage. Entrepreneurs haveaccess to a technology that uses capital and labor for production. In equilibrium, only talentedindividuals with a certain level of wealth choose to become entrepreneurs.

In this paper, we develop a micro-founded general equilibrium model toaddress these issues. This approach oers a consistent framework to elucidate the linkages betweennancial inclusion, GDP, and inequality, and to quantify the impact of specic policy changes.

taking more systemic risk in the pursuit of increasing financial inclusion.

for example, civil conflict, a lack of rule of law, or severe income and wealth inequality cause both low financial inclusion and low growth. Addressing those other issues may help in promoting growth and possibly also inclusion, and promoting the opening of bank accounts and other financial services may not help much and could indeed be harmful

On the users’ side, a number of indicators are examined: share of firms and investment financed by bank credit, share of the population with account at a formal financial institution by gender and by income groups, share of firms citing finance as a major obstacle, share of adults using accounts to receive transfers and wages, share of bank borrowers in the population, and, finally, the extent of the use of insurance products.

On the providers’ side, the index of Financial Institutions Access introduced in Sahay and others (2015a) covered the number of branches of commercial banks and ATMs per 100,000 adults.

As The World Bank (2014) points out, the concept of financial inclusion could range from “access and use of services provided responsibly and sustainably” to “delivery of financial services at affordable costs to disadvantaged and low-income segments of society

Financial Inclusion: Can It Meet Multiple Macroeconomic Goals? Monetary and Capital Markets Department with inputs from Strategy and Policy Review Department and other departments

September 2015

and using five-year averages of all variables to smooth out cyclical variations

Since financial inclusion is a multidimensional concept, its macroeconomic effects depend on its nature. This paper examines the linkages of financial inclusion with economic growth, financial and economic stability, and inequality; it offers three key policy-relevant findings.

Financial Inclusion: Can It Meet Multiple Macroeconomic Goals?

The Solow–Swan model augmented with human capital predicts that the income levels of poor countries will tend to catch up with or converge towards the income levels of rich countries if the poor countries have similar savings rates for both physical capital and human capital as a share of output, a process known as conditional convergence.

Maybe not a ELI5, but: Moments are expectations of things. E(X) is often called the "first moment," E(X2 ) is the "second moment," etc. They can also be more complicated, like E(exp(5x+y)), or whatever. In econometrics, you're trying to figure out something about the underlying distribution of your y's and your x's (and the errors). Often you don't know the shape of the distribution, but you know some moments of the distribution. This is useful because you can't use maximum likelihood estimation unless you make assumptions on the entire distribution. With ordinary least squares, you assume that E(ex) = 0, that is, the errors are uncorrelated with the regressors. You can write e = y - xbeta, to get a moment condition E(x(y-xbeta)) = 0. If you do GMM with this moment condition, you get the regular OLS estimator. If you have endogeneity of some kind, you don't know that E(ex) = 0, but you might have some instruments Z, such that E(ez) = 0. This gives you the moment condition E(z(y - x*beta)) = 0. GMM is nice because it makes relatively weak assumptions compared to other ways of estimating parameters. I hope that helps!

offer poor households access to a cash-flow management facility that combines convenience with capacity. It would provide the chance to make small-scale savings of any value at any time with the right to withdraw on demand; and at the same time it would offer loans of a modest value that can be taken quickly, on demand, at any time, and repaid in small (and if necessary, irregular) installments. – p. 178

Loans can now be "topped up": halfway into a one-year loan repayment, you can borrow back to the full amount.

Portfolios of the Poor. The new book's four authors---Daryl Collins, Jonathan Morduch, Stuart Rutherford, and Orlanda Ruthven---took up an idea of David Hulme, to compile financial diaries of poor households. A researcher visits a poor household repeatedly, say, every fortnight for a year, and gathers detailed information on what its members earned, spent, borrowed, and saved since the last visit.

Much glory in the social sciences goes to those who study causality, who (seem to) show that A causes B. Yet the most enlightening work is often just plain descriptive, coming from a good, long stare at A or B.

It is understood that Excel Force MSC Bhd (EForce), a stockbroking solutions provider, plans to expand into the insurance sector