Sentence examples for big data capital and from inspiring English sources

What is more interesting is that the elasticities of big data capital and big data labour stock are significant, for nearly all coefficients at 5%.

Its main innovation is to develop a more general approach to corporate performance and to the production function, that allows us to answer more directly questions such as the (importance of) complementarity of big data capital and labour.

We thus rather resort to another estimation strategy, whereby we compute the big data capital and labour elasticities εkd and εld for each company that has invested in big data, which we directly correlate with each whether the i-th firm has or not invested in either big data domain.

The performance test relies on a so-called trans-logarithmic production function, allowing for a more direct test of the complementarity between big data capital and big data labour investments; further, we have used a Heckman correction to adjust for the fact that companies investing in big data are generally more productive than their peers.

Log(LD) measure big data capital and labour elasticities; The sign of β2 as well of δ2 measures growing (if positive) or declining (if negative) returns in new big data investments in capital and labour input; The sign of γ, measures the extent of substitution, (if negative) or of complementary (if positive) between big data labour and capital.

Further, the complementarity effect in labour and capital boosts the big data capital elasticity by 50% (1.05%/2.1% = 50%), as well as the big data labour elasticity by more than 70% (1.15%/1.6% = 72%).

We define K = KD+ KND, and L = LD + LND where KND (respectively LND) is the stock of all types of capital, including machinery and IT, but outside big data capital investment (respectively, is the stock of labour outside of the big data workforce).

Including in computation only the statistically significant production parameters at 5%, the complete big data capital elasticity, εkd = β1 + β2.Log KD) + y.log(LD), amounts to: 2.1% + (10.5%*10%) = 3.15%.

The positive sign implies that big data productivity capital and labour elasticities are higher for companies invested in CUST and COMP domains.

A review paper on Internet big data and capital markets by Minjian Ye and Guangzhong Li in this special issue finds that only four papers from the top-3 finance journals - three from Journal of Finance, one from Review of Financial Studies, and none from Journal of Financial Economics – focus on the issues of big data in capital markets.

The second FinTech paper, entitled "Internet big data and capital markets: A literature review", by Minjian Ye and Guangzhong Li, conducts a literature review on the academic publications that are related to the internet big data.