How to interpret the result of the "Total Factor Productivity of Manufacturing Firms" based on Levinsohn and Petrin (2003) approach?

I intend to measure the TFP of manufacturing firms for 23 firms through Cobb - Douglas Production Function Approach using Prodest code in Stata for the period 2015-2017.
I am using Levinsohn and Petrin (2003) approach with the attached Stata dataset for the same. However, I got negative coefficients of logL and logK in case of Levinsohn and Petrin (2003) approach. Results have been attached in the form of the image below. These individual TFP Values as dependent variables are regressed with infrastructure stocks as an independent variable.
Stata Code:

prodest lnGVA, method (lp) free(lnL) proxy(lnInput) state(lnK) poly(3) valueadded reps(250)

predict TFP

Can anyone help to overcome this issue in the result? Please respond.

Famid	year	lnGVA	lnK	lnL	lnInput
1	2015	13.34451139	14.43711069	13.82499642	14.94789177
2	2015	10.90103056	11.39432509	12.00363817	12.56028455
3	2015	10.52884158	10.90823019	11.74051512	12.56156862
4	2015	11.71408167	12.96707595	11.86919333	13.19120632
5	2015	10.78025708	10.57660072	11.29931136	12.61370021
6	2015	11.30195799	10.79404052	10.71557266	12.07061138
7	2015	13.89161883	14.69274188	13.91372923	15.59004602
8	2015	12.68505841	13.08795162	13.27239071	14.34357928
9	2015	12.17481436	12.49800879	11.90358822	13.0876142
10	2015	10.37213186	10.36546633	10.85971028	11.51539809
11	2015	11.89178185	12.93752458	11.87475212	13.15976277
12	2015	12.88529455	13.74124074	13.52565546	14.57748312
13	2015	11.26551282	11.99049128	12.59243988	13.35132999
14	2015	11.91772596	13.18896836	12.4565356	13.65617625
15	2015	14.08798489	14.43171365	14.08198176	15.39174269
16	2015	11.84720763	14.04701543	12.27763023	13.27226267
17	2015	11.84987474	12.32818954	13.05611887	13.71366131
18	2015	12.2899301	12.94906791	12.83675914	13.8142172
19	2015	13.31159488	14.0107976	14.37021545	14.99198913
20	2015	7.930242796	7.485056583	10.17564981	8.622648785
21	2015	12.58255248	13.30226199	13.42014082	14.52482222
22	2015	12.45019737	12.54385883	12.59546596	13.57663852
23	2015	11.82869258	13.06866314	13.13062515	14.08698579
1	2016	13.48373632	14.55212104	13.81087483	14.87352281
2	2016	11.09011635	12.09660422	12.06294103	12.5021024
3	2016	10.43491923	10.92367085	11.54507315	12.3586785
4	2016	11.26804467	13.0838402	11.83438558	13.05207522
5	2016	10.7530443	10.4765827	11.23227197	12.73695465
6	2016	11.41296781	10.8661762	10.80685514	12.14263568
7	2016	13.9810047	14.90279048	13.99064468	15.47850878
8	2016	12.75290698	13.25330751	13.23466654	14.43921191
9	2016	12.17262238	12.62311498	11.81393335	12.95478697
10	2016	10.49895051	10.55531489	10.86526777	11.58579992
11	2016	11.52578885	12.93922703	11.86191193	13.20034564
12	2016	12.99481134	13.78688988	13.55250289	14.51278126
13	2016	11.53622211	12.27852734	12.51736626	13.27750928
14	2016	12.20480924	13.55141515	12.49875718	13.69012924
15	2016	14.14469829	14.47629798	14.13122964	15.45322844
16	2016	11.80136403	14.22621284	12.25082132	13.35906515
17	2016	11.91459215	12.41077943	13.10543896	13.69703396
18	2016	12.39233098	13.06787942	12.88085472	13.9162249
19	2016	13.50721806	14.10146753	14.47325385	14.97086086
20	2016	7.590132471	7.815032882	10.07225939	8.626449627
21	2016	12.79879814	13.47297179	13.50166245	14.52501448
22	2016	12.73090918	12.64631381	12.64053977	13.87087559
23	2016	12.05060545	13.1477183	13.11664506	14.11136877
1	2017	13.37820655	14.57031481	13.87654921	14.99791944
2	2017	11.31482949	11.94872061	12.1067936	12.48835749
3	2017	10.48552974	11.50844226	11.50258216	12.33606399
4	2017	11.45326146	13.4451234	11.89512877	13.13305958
5	2017	10.53909949	10.41244812	11.2286642	12.71520385
6	2017	11.32904661	10.91523748	10.70495088	11.98065828
7	2017	13.91086343	15.06872287	14.03587425	15.54622029
8	2017	12.98490547	13.39216318	13.3848061	14.65935721
9	2017	12.08523011	12.39343758	11.86197541	12.95263912
10	2017	10.6732993	10.92220152	10.98576719	11.73012375
11	2017	11.90939933	13.25324863	11.88186489	13.18303098
12	2017	13.19309476	13.82810032	13.62542212	14.61800501
13	2017	11.72306923	12.43306157	12.42895616	13.41005668
14	2017	12.21973581	13.62180352	12.54387614	13.72163599
15	2017	14.10537468	14.43870418	14.12643932	15.34049703
16	2017	12.04438547	14.43877548	12.31398041	13.40533761
17	2017	11.98871848	12.33912744	13.18484604	13.69294326
18	2017	12.53221462	13.23962174	12.93065551	14.01079714
19	2017	13.5782688	14.25990109	14.51053547	15.04941816
20	2017	7.673050689	7.846913183	10.08397409	8.60560012
21	2017	13.23123952	13.50385468	13.57157867	14.59337051
22	2017	12.61675213	12.68825504	12.74948936	13.66224058
23	2017	12.22915794	13.35048112	13.11830917	14.14173054